AB-100 Agentic AI Business Solutions Architect

Plan AI-powered business solutions

Testlet 1

Case study

Overview

Contoso, Ltd. is a high-tech manufacturing company that uses Microsoft Dynamics 365 Finance. Dynamics 365 Supply Chain Management, and Dynamics 365 Commerce for its North American operations. The company designs and develops innovative products that have many patents and proprietary technologies. The patents and engineering designs are closely guarded secrets.

Contoso executives want to integrate and adopt AI solutions to help scale the company in preparation for an anticipated period of rapid growth.

The company has multiple legal entities and Azure subscriptions that will be used in the adopted AI solutions.

Requirements

AI Adoption

The following executives will have specific responsibilities in the overall AI adoption:

• Chief Technology Officer (CTO): Select one Dynamics 365 Finance, Dynamics 365 Supply Chain Management or Dynamics 365 Commerce prebuilt AI agent and one custom Microsoft Copilot Studio AI agent to prioritize and deploy during the initial AI adoption phase.

• Chief Information Officer (CIO): Ensure that appropriate security labels are assigned to the data used by the AI agents.

• Chief Financial Officer (CFO): Analyze the return on investment (ROI) for the AI agents being deployed. Chief Information Security Officer (CISO): Discover and inventory AI resources for auditing.

• Chief Executive Officer (CEO): Ensure that all solutions adhere to industry-standard responsible AI practices.

All AI initiatives and agents will have a detailed business use case, a defined audience profile, and an estimated ROI that will compare the cost savings of the current process against the estimated costs of using the new AI solutions.

The company's research and development (R&D) department already has a custom Model Context Protocol (MCP) server that contains comprehensive product specifications and compliance data.

Prebuilt AI Agent

The CTO has NOT yet selected which prebuilt AI agent to use in Dynamics 365 Supply Chain Management. The CTO wants to view available agent templates to identify which agent will add the most business value.

Depending on which high-priority AI agents are identified, its agent capabilities must be previewed in a discovery meeting with the relevant business operation stakeholders.

Custom AI Agent

Contoso has identified the following custom AI agent requirements:

• The custom AI agent will use data from Dynamics 365 Supply Chain Management to answer questions for the manufacturing team as a low-code solution.

• The custom AI agent will be accessible from within Microsoft Teams.

• The custom AI agent must be designed to eventually connect to other agents that can be selected based on their description.

• The topics used in the custom AI agent will be selected based NOT on a trigger phrase, but on a description of the purpose of the query, to make the interactions more conversational.

• The custom AI agent must be able to answer questions about product specifications by using existing technologies. The product specifications are maintained by the R&D department.

• The custom AI agent must be integrated with and accessible from Dynamics 365 Supply Chain Management.

• The custom AI agent must be able to use Dynamics 365 Supply Chain Management business logic that is stored outside of the application.

Analysis, Reporting, and Troubleshooting

Contoso has identified the following analysis, reporting, and troubleshooting requirements:

The CISO will audit all the AI solutions monthly for compliance and security.

The CFO will analyze all the AI solutions quarterly to compare the estimated ROI against actual measured efficiencies and adoption. The CFO will use the Copilot Studio agent usage estimator to perform this analysis.

The CISO wants to identify how much sensitive data was accessed for a given AI agent run and who accessed the data. Too much sensitive data accessed by a single user might indicate a high security risk.

The CTO wants to track user feedback on the quality of the AI agent responses during user interactions with the agents. Consistently poor feedback will trigger an escalated reengineering discussion.

The CEO wants a quarterly assessment of all the required metrics for their specific responsibilities. The tools used for the assessments must be Microsoft-recommended and must verify reliability, interpretability, fairness, and compliance.

The CFO wants to identify how many interactions with the AI agents are abandoned on a given day as compared to resolved conversations. Too many abandoned sessions might indicate that Copilot Studio credits are being used inefficiently by end users.

QUESTION 1

Which two components in the custom AI agent design should the CFO evaluate in the quarterly agent analysis? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. the GPT models used for the agent

B. the average characters in a chat message

C. the agent orchestration method

D. the average session time per agent

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C, D

The CFO’s quarterly analysis is focused on comparing:

• estimated ROI

• actual measured efficiencies

• actual adoption

The case study explicitly says the CFO will use the Copilot Studio agent usage estimator . For that kind of analysis, the most relevant design components are the ones that affect how the agent is used operationally and how interactions are processed.

Quarterly Estimated ROI (Forecasting)

Use the Microsoft Agent Usage Estimator to model quarterly expectations before each period.

Orchestration Method Input: Select between Classic (logic-driven) or Generative (AI-driven) orchestration. Generative orchestration typically consumes more credits but reduces manual development time.

Session Time Variables: Model the average session time per agent to estimate total message volume. The estimator uses this to project credit consumption based on interaction depth.

Target ROI Formula: Define the benchmark as:

Estimated Savings = (Projected Deflection × Human Agent Cost) - Estimated Credit Cost.

Why C. the average session time per agent is correct:

Average session time is a practical usage and adoption indicator. It helps the CFO understand how much users are engaging with the agent and whether the agent is reducing effort efficiently or creating long, costly interactions.

Why D. the agent orchestration method is correct:

The orchestration method affects how the agent handles requests, invokes tools, uses knowledge sources, and consumes resources. Since this can influence both operational efficiency and cost, it is important for ROI analysis.

Why the other options are not the best fit:

QUESTION 2

What should you configure for the custom AI agent?

A. AI-assisted evaluators

B. classic orchestration

C. generative orchestration

D. Azure OpenAI reasoning models

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Correct Answer: C

Explanation/Reference:

Explanation:

Generative orchestration is the most appropriate choice for this Microsoft Dynamics 365 AI agent solution. This selection directly addresses your requirements for a low-code, conversational, and interconnected agent ecosystem within the Microsoft Power Platform and Dynamics 365 environment.

Why Generative Orchestration?

Generative orchestration (available in Microsoft Copilot Studio) is specifically designed to move away from rigid, trigger-phrase-based logic toward a flexible, intent-based model.

Mapping to Your Requirements

Intent-Based Selection: Unlike "Classic" orchestration which relies on exact trigger phrases, generative orchestration uses Natural Language Understanding (NLU). It selects the correct topic or "sub-agent" based on a description of the purpose, allowing for the conversational flow you requested.

Low-Code Integration: Copilot Studio is the primary low-code tool for Dynamics 365. It provides native connectors to Supply Chain Management (SCM) data and can be embedded directly into the SCM interface or deployed to Microsoft Teams.

External Business Logic: It can trigger Power Automate flows or API calls to execute business logic stored in external databases or legacy systems, bringing that data back into the conversation.

Product Specifications: By using Generative Answers, the agent can crawl "existing technologies" like SharePoint libraries, internal wikis, or SCM data tables to answer complex spec questions without manual topic authoring.

Incorrect:

[Not A]

AI-Assisted Evaluators are testing and diagnostic tools, not runtime execution engines.

You would use these to measure how well your agent is performing, but they cannot be the agent or manage the logic flow.

[Not B]

Classic Orchestration is entirely dependent on trigger phrases.

It creates a "command-and-control" feel rather than the fluid, conversational interaction you are looking for.

It also scales poorly when trying to connect multiple agents.

[Not D]

Azure OpenAI Models (Reasoning Models) while powerful, this is a pro-code path (API-heavy).

Using raw Azure OpenAI models would require significant custom development, missing the "low-code" requirement. While Generative Orchestration uses these models under the hood, the orchestration layer itself is what manages the "which agent to call" logic.

Scenario: Custom AI Agent

Contoso has identified the following custom AI agent requirements:

*-> The custom AI agent will use data from Dynamics 365 Supply Chain Management to answer questions for the manufacturing team as a low-code solution.

The custom AI agent will be accessible from within Microsoft Teams.

The custom AI agent must be designed to eventually connect to other agents that can be selected based on their description

*-> The topics used in the custom AI agent will be selected based NOT on a trigger phrase, but on a description of the purpose of the query, to make the interactions more conversational.

The custom AI agent must be able to answer questions about product specifications by using existing technologies. The product specifications are maintained by the R&D department.

*-> The custom AI agent must be integrated with and accessible from Dynamics 365 Supply Chain Management.

*-> The custom AI agent must be able to use Dynamics 365 Supply Chain Management business logic that is stored outside of the application.

Plan AI-powered business solutions

Background

Fabrikam, Inc., is a global consumer goods company that is undergoing a digital transformation initiative to migrate its entire infrastructure to the Microsoft cloud. As a key element of this cloud migration, the company will implement Microsoft Dynamics 365 Sales, moving away from the current on-premises proprietary technologies used by its business-to-business (B2B) sales team.

As part of the cloud migration, Fabrikam will adopt an AI-first approach to its business solutions and implement AI solutions, wherever possible, to streamline operations.

Problem Statements

Fabrikam's infrastructure currently relies on various on-premises systems that require sales executives to use corporate computers with physical keyboards to access business information during customer interactions. Mobile phones cannot be used for these purposes, as the systems depend on keyboard input. As a result, the sales executives spend a lot of time using keyboards to search for data on several disparate systems and file servers, rather than focusing on the customers. This affects the customer experience.

Fabrikam stakeholders are concerned that users will be hesitant to adopt AI. If the AI initiatives are NOT adopted, cost savings will never be realized. Additionally, funding for future AI initiatives will depend on demonstrating an increase in AI adoption month over month. As the AI agent initiative for the sales team will be the first for Fabrikam, the rapid adoption of the agent is a high priority

Planned Initiatives

General

Fabrikam management has prioritized AI-driven projects to improve efficiency, customer engagement, and responsible AI adoption. The current application infrastructure is on-premises and must be migrated to the cloud to support the adoption of these technologies.

Infrastructure Migration

Fabrikam plans to migrate from its current on-premises infrastructure to a completely cloud-based topology; this will include user authentication, the security framework, and, primarily, the adoption of the services by end users.

All the data from the different systems will be consolidated into a single data source - a common data model that will use a Microsoft Dataverse environment as a single source of truth (SSOT) for the sales team.

Sales Cycle Enablement

To achieve the company's objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle:

Use low-code development to create a single AI agent that has Dataverse as its core component. Ensure that sales managers can access unanswered correspondence from prospects and intervene as appropriate.

Replace the previous proprietary software with Dynamics 365 Sales to track sales cycles and customer interactions.

Have the sales executives use Dynamics 365 Sales to track interactions for open opportunities and send follow-up communications to prospects.

Have the sales executives use handsfree headsets to interact with an AI agent when they have questions about internal policies or customer data.

Requirements

Infrastructure Migration

Fabrikam has identified the following infrastructure migration requirements:

Azure must be used for all future infrastructure workloads.

The company must follow Microsoft-recommended methodologies for infrastructure migration to the cloud.

Any created AI agents must have their return on investment (ROI) calculated to ensure that the solution will save the company money.

Sales Cycle Enablement

Fabrikam has identified the following requirements for sales cycle enablement:

The final AI agent must follow Microsoft recommendations for a conversational user experience.

A designated checklist must be reviewed to ensure that the AI agent follows Microsoft deployment recommendations for a compliant solution.

Detailed telemetry must be logged for the first created AI agent to help troubleshoot and optimize the agent during the initial AI agent adoption process.

Unexpected AI agent actions must end in an escalation to a live representative. For example, a sales executive must be rerouted to a representative if the agent cannot answer a question after two failed attempts.

The return on investment (ROI) of switching from the current process to the future process is required for stakeholder sign off.

The sales team must use Dynamics 365 Sales to correspond with prospects more quickly and efficiently than currently.

Sales managers must report on the adoption of the AI agent to key Fabrikam stakeholders on a monthly basis.

Any sensitive information, such as user IDs and names, shared via the AI agent must be tracked for future auditing.

QUESTION 1

Which framework should you use to meet the AI agent requirements for the sales cycle enablement? To answer, select the appropriate options in the answer area.

Hot Area:

Answer Area

For Microsoft Copilot Studio best practices:

• the ALM Accelerator for Microsoft Power Platform
• Microsoft Cloud Adoption Framework for Azure
• Microsoft Power Platform Well-Architected framework
• Success by Design

For conversational user experiences:

• the ALM Accelerator for Microsoft Power Platform
• Microsoft Cloud Adoption Framework for Azure
• Microsoft Power Platform Well-Architected framework
• Success by Design

Explanation/Reference:

Explanation:

Box 1: the ALM Accelerator for Microsoft Power Platform For Microsoft Copilot Studio best practices

Using the ALM Accelerator for Microsoft Power Platform is a recommended approach for managing the lifecycle of a low-code AI agent (Copilot Studio) that relies on Dataverse. It enables source control, versioning, and automated deployment of AI agents to ensure they follow Microsoft's best practices.

Box 2: Microsoft Power Platform Well-Architected framework For conversational user experience

Utilizing the Microsoft Power Platform Well-Architected framework for a low-code AI agent (built in Copilot Studio) with Dataverse as the core data component ensures the solution is secure, reliable, and provides a high-quality conversational user experience (CUX). The framework helps align the agent with Microsoft’s best practices for responsible AI, efficiency, and user satisfaction.

Scenario: Sales Cycle Enablement

Fabrikam has identified the following requirements for sales cycle enablement:

*-> The final AI agent must follow Microsoft recommendations for a conversational user experience.

Sales Cycle Enablement

To achieve the company's objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle

*-> Use low-code development to create a single AI agent that has Dataverse as its core component.

QUESTION 2

Which framework should you use for the infrastructure migration?

A. Microsoft Cloud Adoption Framework for Azure

B. Success by Design

C. Microsoft Power Platform Center of Excellence (CoE)

D. Microsoft Power Platform Project Setup Wizard

Correct Answer: A

Explanation/Reference:

For migrating a legacy on-premises infrastructure to Microsoft Dynamics 365 Sales with Dataverse as the Single Source of Truth (SSOT), the recommended framework is the Microsoft Cloud Adoption Framework for Azure (CAF), specifically utilized in conjunction with the Data Management Framework (DMF) for Dynamics 365.

This combined approach ensures a structured transition by focusing on both the strategic adoption of cloud technology and the technical, granular migration of data.

Recommended Framework: Microsoft Cloud Adoption Framework (CAF) The CAF provides a holistic structure to ensure the migration is secure, compliant, and aligned with business goals.

Plan: Assess legacy data, prioritize workloads, and define the SSOT requirements.

Ready: Set up the Dataverse environment (landing zone) and configure security (Azure Active Directory/ Microsoft Entra ID).

Adopt (Migrate): Perform the technical migration of data using ETL (Extract, Transform, Load) processes.

Scenario: Infrastructure Migration

Fabrikam plans to migrate from its current on-premises infrastructure to a completely cloud-based topology; this will include user authentication, the security framework, and, primarily, the adoption of the services by end users.

All the data from the different systems will be consolidated into a single data source - a common data model that will use a Microsoft Dataverse environment as a single source of truth (SSOT) for the sales team.

Background

Fabrikam, Inc., is a global consumer goods company that is undergoing a digital transformation initiative to migrate its entire infrastructure to the Microsoft cloud. As a key element of this cloud migration, the company will implement Microsoft Dynamics 365 Sales, moving away from the current on-premises proprietary technologies used by its business-to-business (B2B) sales team.

Reference:

Plan AI-powered business solutions

QUESTION 1

A company uses Microsoft Dynamics 365 Sales to manage leads that are stored in a Microsoft Dataverse table named Lead and use non-standard terminology and custom columns.

You need to configure business terms in the Lead table so that Microsoft Copilot controls can summarize the leads efficiently. The solution must minimize administrative effort.

How should you configure the business terms?

A. Combine all the fields into one custom field.

B. Map the field display names as business terms.

C. Add the schema names as business terms.

D. Create new business terms for each field.

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Correct Answer: B

Explanation/Reference:

To configure Microsoft Copilot to efficiently summarize leads with non-standard terminology and custom columns in Microsoft Dynamics 365 Sales, you must map these unique fields to business terms within the Sales AI Glossary in Microsoft Copilot Studio.

Note:

To map your field display names as business terms:

1. Access Copilot Studio: Open Microsoft Copilot Studio and select the environment containing your Dynamics 365 Sales instance.

2. Select the Sales Agent: Navigate to Agents and select the agent named Copilot in Dynamics 365 Sales (formerly Sales Copilot Power Virtual Agents Bot).

3. Navigate to Knowledge: Under the Knowledge section, select the SalesSpecificQnA knowledge source.

4. Add Glossary Entries:

Go to the Glossary tab.

Term: Enter the non-standard or custom field display name (e.g., your custom business term).

Description: Define how this term relates to the Dataverse schema. This helps Copilot understand the logic behind the custom column.

1. Configure Synonyms: In the Synonyms section, map your custom field to alternative names that sellers might use in natural language queries (e.g., mapping "Custom Revenue" to "Opportunity Revenue").

2. Publish Changes: Select Publish to apply these mappings, allowing Copilot to use the newly defined terms when generating lead summaries.

QUESTION 2

You are designing two Microsoft Copilot Studio agents named Agent1 and Agent2. Each agent must meet the following requirements:

Each agent must use a standard model.

Each agent must NOT use generative orchestration.

Agent1 must support simple and short phrases for a given topic.

Agent2 must integrate with Microsoft Dynamics 365 Contact Center voice channel.

You need to recommend language models for the agents.

What should you recommend for each agent? To answer, drag the appropriate language models to the correct agents. Each language model may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Select and Place:

Language models

• Azure Language in Foundry Tools
• Azure OpenAI
• Conversational language understanding (CLU)
• Natural language understanding (NLU)
• Natural language understanding + (NLU+)

Answer Area

• Agent1:
• Agent2:

---

Box 1: Natural Language Understanding (NLU)

Box 2: Natural Language Understanding + (NLU +)

Explanation/Reference:

Box 1: Natural Language Understanding (NLU)

Agent1 must support simple and short phrases for a given topic.

For a Microsoft Copilot Studio agent that must not use generative orchestration and requires support for simple, short trigger phrases, the best choice is the Classic NLU (Natural Language Understanding) model.

When you disable generative orchestration (also known as "Generative mode" or "Generative AI" orchestration), the agent reverts to Classic orchestration. In this mode, the agent relies on predefined trigger phrases to map user input directly to specific topics.

Box 2: Natural Language Understanding + (NLU +)

Agent2 must integrate with Microsoft Dynamics 365 Contact Center voice channel.

For a Microsoft Copilot Studio agent using classic orchestration (no generative orchestration) and integrating with the Dynamics 365 Contact Center voice channel, the best language model is NLU+.

Why NLU+ is the Best Choice While standard agents offer three "classic" Natural Language Understanding (NLU) options, NLU+ is specifically designed for high-performance, enterprise-grade scenarios like voice channels.

Note:

Comparison of Classic Models

Model	Best For	Key Characteristic
NLU	Simpler bots	Uses 5-20 phrases per topic; basic RegEx/List entities.
NLU+	Voice / Enterprise	Optimizes speech recognition and handles large training sets with high accuracy.
CLU	Advanced devs	Integrates with Azure Conversational Language Understanding for external model management.

QUESTION 3

A company uses Microsoft Dynamics 365 finance and operations apps.

The company plans to use Microsoft Copilot in-app help and guidance to generate responses for internal business processes.

You need to add an additional knowledge source for the business processes. The solution must NOT add new topics to the Copilot agent for the finance and operations apps.

Which knowledge source should you add?

A. Microsoft Dataverse

B. a public website

C. Azure AI Search

D. a file upload

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Correct Answer: D Section: (none)

Explanation/Reference:

Explanation:

To add an additional knowledge source for internal business processes to the Microsoft Copilot in-app experience for Dynamics 365 finance and operations apps—without creating new topics—you should add File Uploads (such as PDF, Word, or text documents) to the "Copilot for finance and operations apps" agent in Copilot Studio.

QUESTION 4

A company has an AI business solution.

You need to extend the solution so that Microsoft 365 Copilot can invoke external logic hosted in Azure services.

What should you include in the solution?

A. Microsoft Copilot Studio skills

B. Microsoft Power Platform connectors

C. custom engine agents

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Correct Answer: B Section: (none)

Explanation/Reference:

Explanation:

To enhance an AI business solution with Microsoft 365 Copilot and integrate external logic hosted in Azure, you should use Copilot Studio to create Actions. These actions act as plugins that allow Copilot to invoke external services through Power Platform components.

Implementation Strategy

Azure Logic Hosting: Host your external logic in Azure using services like Azure Functions or Azure Logic Apps. These provide the API endpoints that Copilot will ultimately call.

*-> Power Platform Connector: Create a Custom Connector in the Power Platform to wrap your Azure service's API. This connector acts as the bridge, translating Copilot's requests into API calls your Azure logic understands.

Copilot Studio Integration: Within Microsoft Copilot Studio, add the custom connector as a Tool or Action. This makes the logic discoverable and invokable by Microsoft 365 Copilot.

Deployment: Deploy the action through the Microsoft 365 admin center under Integrated Apps to make it available to users in Teams or other Microsoft 365 apps.

Key Components *->

Connector: Wraps the Azure API using an OpenAPI definition or Postman collection.

Plugin/Action: Defines how Copilot identifies when to use the connector based on user prompts.

Authentication: Ensure the connector is configured with appropriate security (e.g., OAuth 2.0) to safely access your Azure resources.

QUESTION 5

You need to design a shared prompt library that will be used across multiple business units. The solution must meet the following requirements:

• Ensure consistent AI responses with reusable formats.
• Support governance and version control.
• Minimize administrative effort.
• Minimize ongoing costs.

What should you recommend for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

Answer Area

Ensure consistent AI responses:

• Delegate department-specific prompt templates.
• Define standardized prompt templates.
• Maintain a prompt history.

Support governance and version control:

• Define standardized prompt templates.
• Store prompts in a Git repository.
• Categorize prompts by business function.

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Box 1: Define standardized prompt templates

Box 2: Store prompts in a Git repository

Explanation/Reference:

Explanation:

Box 1: Define standardized prompt templates

Ensure consistent AI responses with reusable formats.

To ensure consistent AI responses across multiple business units, your shared prompt library should be built on a foundation of standardized, modular templates that balance centralized governance with unitspecific flexibility.

Box 2: Store prompts in a Git repository

Support governance and version control.

Storing AI prompts in a Git repository allows you to treat prompts as "first-class artifacts" with the same accountability and lifecycle management as source code. For an enterprise solution serving multiple business units, this approach provides the necessary structure for governance, collaboration, and scalability.

1. Repository Organization for Business Units

2. Governance and Version Control Workflow Branching Strategy: Use a dedicated branch for each experiment or new use case (e.g., feature/ marketing-seo-v2) to ensure the main branch remains stable.

Pull Requests (PRs): Mandate PRs for all changes to enable peer reviews. PRs should include descriptions of changes, linked issues, and test results.

Semantic Versioning: Apply tags (e.g., v1.0.1) to mark significant updates, allowing business units to pin their applications to specific, stable prompt versions.

Auditability: Git maintains a full historical record of who changed a prompt, what was modified, and when it occurred.

QUESTION 6

A company has a Microsoft Foundry project that uses a single agent and a single prompt to complete a series of tasks.

The agent encounters the following issues:

• It frequently produces incomplete results.
• It struggles with domain-specific reasoning.
• Agent response times are remarkably slow.

You need to recommend a solution to improve the overall performance and accuracy of the agent.

What should you include in the recommendation?

To answer, drag the appropriate actions to the correct requirements. Each action may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Select and Place:

Actions

• Add a grounding data source.
• Add a prebuilt connector.
• Move to a multi-agent architecture.
• Upgrade to a larger generative AI model.

Answer Area

• To improve performance: [______]
• To improve accuracy: [______]

Action

• [______]
• [______]

---

Box 1: Move to a multi-agent architecture

Box 2: Add a grounding data source

Explanation/Reference:

Box 1: Move to a multi-agent architecture To improve performance

To improve performance

Moving to a multi-agent architecture in Azure AI Foundry is a highly effective strategy to overcome performance bottlenecks, as single-agent systems often struggle with long-running tasks, leading to high latency and timeout issues. By decomposing complex tasks into smaller, specialized subtasks, you can improve response times through parallel processing and targeted tool usage.

Incorrect:

Upgrade to a larger generative AI model

To address slow response times in your Microsoft Foundry agent, upgrading to a larger generative AI model is one option, but it may increase latency in some scenarios due to higher processing demands. Instead, a combination of prompt optimization, model selection, and architectural changes in Microsoft Foundry is recommended to improve performance.

Box 2: Add a grounding data source

To improve accuracy

To improve the performance of an agent in a Microsoft Foundry project experiencing incomplete results, weak domain reasoning, and high latency, adding a grounding data source is a highly effective strategy. Grounding connects the Large Language Model (LLM) to verified external data, ensuring responses are accurate, contextual, and less likely to hallucinate.

QUESTION 7

A financial services company uses Microsoft Dynamics 365 Finance.

Currently, the company's support staff manually reviews customer transaction histories to detect potential fraud cases before escalating the cases.

You need to recommend an automation solution for the review process. The solution must ensure that escalations reach a human analyst for final decision making. What should you recommend?

A. Deploy an autonomous agent that closes non-fraud cases automatically.

B. Use Microsoft 365 Copilot in Word to automatically finalize fraud detection policies.

C. Configure a task agent to generate fraud risk scores for the human analyst to review.

D. Export the data to a data lake for analysis in Microsoft Power BI.

---

Correct Answer: C

Explanation/Reference:

Explanation:

To automate the fraud review process in Microsoft Dynamics 365 Finance while ensuring a human analyst makes the final decision, you should configure the Dynamics 365 Fraud Protection (or integrated Copilot AI agents) to generate risk scores and route high-risk transactions to a manual review queue.

Here is the configuration approach to achieve this:

1. Implement AI-Driven Risk Scoring: Utilize Dynamics 365 Fraud Protection, which uses AI to analyze customer transaction history and assign a risk score (0-999) to each transaction.
2. Define Rules for Escalation: Set up fraud rules in the system to determine which transactions require human intervention. For instance, define a threshold (e.g., a "Minimum score value") where transactions with high fraud probability are automatically flagged.
3. Establish Manual Review Queues: Configure the Manual Review tool to create queues for suspected fraudulent transactions, allowing human analysts to review the AI-generated risk score and transaction history, such as customer behavior, for final, informed decision-making.
4. Use Copilot/AI Agents for Monitoring: Enable AI agents to continuously monitor financial data, such as invoice, payment, and vendor data, and generate alerts for unusual patterns before escalating.

This setup, particularly through the Manual Review workspace, allows for an automated, intelligent, and scalable approach to fraud management.

QUESTION 8

A company plans to deploy a Microsoft Copilot Studio agent that will analyze historical business data to predict customer behavior.

The data is currently stored in an Azure SQL database, flat files, APIs, and logs.

You need to organize the data into a format that can be used as a knowledge source in Copilot Studio.

What should you include in the solution?

A. Azure AI Search

B. Azure Data Lake Storage

C. Azure Cosmos DB

D. Azure Translator in Foundry Tools

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Correct Answer: A

Explanation/Reference:

Microsoft Copilot Studio agents can analyze customer behavior by leveraging business data from Azure SQL, files, and APIs by using Azure AI Search as a knowledge source. By importing and vectorizing this structured and unstructured data into an Azure AI Search index, the agent can perform semantic, meaning-based searches to retrieve context-relevant information.

QUESTION 9

A retail company plans to deploy Microsoft Copilot Studio agents to support:

• Microsoft Dynamics 365 Commerce scenarios.
• A Microsoft Power Apps inventory management solution.

You need to recommend a solution to organize product catalog data as a consistent source for multiple AI systems.

What should you recommend?

A. Let each agent scrape product details from Microsoft SharePoint Online libraries.

B. Store the product catalog data in a separate custom table for each agent.

C. Configure prompts to pull product details from the PDFs of external vendors.

D. Centralize the product catalog data in Microsoft Dataverse and expose the data to both agents.

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Correct Answer: D

Explanation:

In the scenario described, centralizing product catalog data in Microsoft Dataverse is the recommended architectural approach to ensure consistency across multiple AI systems. Dataverse acts as a unified "knowledge network" that allows different agents to share a single source of truth for both structured and unstructured data.

Key Benefits of Centralizing in Dataverse

Cross-App Consistency: By storing the catalog in Dataverse, both the Dynamics 365 Commerce agent and the Power Apps inventory management agent access the exact same records. This prevents data silos where inventory levels or product descriptions might drift apart between systems.

Native Copilot Studio Integration: You can directly add Dataverse tables as knowledge sources in Microsoft Copilot Studio. This allows agents to use Retrieval-Augmented Generation (RAG) to answer queries grounded in your live product data.

Security & Governance: Dataverse enforces Role-Based Access Control (RBAC), ensuring that agents only interact with data they are authorized to see, based on the user's existing permissions.

Automated Updates: You can use Power Platform Dataflows to ingest and synchronize catalog data from external sources into Dataverse, keeping the information fresh for all connected AI agents.

QUESTION 10

A company has a portfolio of AI initiatives at different stages of development.

You need to recommend a structured approach to evaluating the return on AI investment (ROAI) across all the initiatives. The solution must balance immediate results with long-term values and strategic innovations.

What should you include in the recommendation?

A. a simple cost and benefit analysis

B. a horizon-based framework

C. the internal rate of return (IRR) function

D. a prioritization grid

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Correct Answer: B

Explanation/Reference:

In this scenario, a horizon-based framework is best for evaluating the return on AI investment (ROAI). While a prioritization grid is excellent for immediate tactical choices (e.g., effort vs. impact), a horizonbased framework is specifically designed to balance diverse timeframes—mapping immediate efficiency gains alongside the long-term strategic and transformational value required for a comprehensive Microsoft AI portfolio.

Why the Horizon-Based Framework Wins

This approach categorizes AI initiatives into three distinct "horizons," allowing you to measure different types of value across the development lifecycle:

Horizon 1: Core Operations (Immediate ROI)

Focuses on extending current capabilities for rapid results, such as using Microsoft Copilot to automate routine coding tasks or IT support.

Horizon 2: Adjacent Opportunities (Mid-Term Value)

Targets growth by expanding into new areas related to your core, such as developing agentic platforms or AI-driven specialized tools that build on existing infrastructure.

Comparison for This Scenario

Horizon 3: Transformational Innovation (Long-Term Strategy)

Invests in "future-forward" innovations that may have uncertain immediate returns but offer massive strategic upside or business model reimagination.

Feature	Priority Grid (e.g., 2x2 Matrix)	Horizon-Based Framework
Primary Goal	Selecting "what to do first" based on constraints.	Managing a balanced portfolio of value over time.
Best For	Tactical, sprint-level feature ranking.	Strategic roadmap and investment allocation.
ROAI Focus	Often emphasizes "quick wins" and high-certainty projects.	Validates high-risk, high-reward innovations as essential for long-term health.

Recommendation: Use the Microsoft AI Maturity Model to baseline your current state, then apply the Horizon-Based Framework to structure your ROAI evaluation. This ensures you don't starve long-term innovation in favor of only "low-hanging fruit" efficiency projects.

QUESTION 11

You need to recommend a Microsoft Power Platform business solution that consolidates data from multiple internal and external data sources. The solution must meet the following requirements:

• Provide the data as a centralized source for multiple AI systems, including Microsoft Copilot Studio agents, Dynamics 365 applications, and external AI models.
• Support built-in data classification and protection policies.
• Provide data for grounding and analytics.

What should you include in the recommendation?

A. Microsoft Dataverse

B. Azure Data Lake Storage

C. a Microsoft Power BI semantic model

D. Azure Cosmos DB

---

Correct Answer: A

Explanation/Reference:

Microsoft Dataverse is the ideal foundational component for this scenario, serving as the secure, centralized data platform for the Microsoft Power Platform, Dynamics 365, and AI integrations. By using Dataverse, the business can consolidate, protect, and utilize data across Copilot Studio agents, Dynamics 365 applications, and analytics tools, addressing all stated requirements.

Here is how Dataverse fulfills the requirements in the described scenario:

Centralized Source: It serves as the primary data storage and management engine for Power Platform, Dynamics 365, and Copilot Studio. It consolidates data into a unified data model (Common Data Model), ensuring consistency across internal and external sources.

Internal & External Integration: Dataverse supports data integration from diverse sources using tools like Power Query, Azure Data Factory, and virtual tables that map external data in real-time.

Data Classification & Protection: It features built-in, enterprise-grade security.

AI Grounding & Analytics:

• Grounding: It acts as the knowledge source for Copilot Studio agents, providing the necessary business context for accurate generative AI responses.

• Analytics: It integrates natively with Power BI for reporting and can synchronize with Microsoft Fabric or Azure Synapse for large-scale data modeling and advanced analytics.

QUESTION 12

A company plans to deploy an AI-based customer service app that will autonomously manage interactions, escalate complex cases, and learn from historical ticket data.

You need to perform a return on AI investment (ROAI) analysis of the app deployment. The solution must ensure that the analysis is accurate.

What should you do first?

A. Establish the AI performance metrics.

B. Conduct an AI market benchmarking study.

C. Model the customer experience.

D. Identify and quantify all the development, deployment, and operating costs.

---

Correct Answer: D

Explanation/Reference:

Explanation:

To conduct a robust Return on AI Investment (ROAI) analysis for your Microsoft-based AI customer service application, you must first categorize and quantify three distinct cost phases: Development, Deployment, and Operations. For a system capable of managing complex escalations and learning from historical data, your project aligns with "Advanced" or "Agentic" AI profiles.

1.Development Costs (Upfront Investment)

This phase covers the creation of the core AI logic, custom integrations, and data preparation.

2.Deployment Costs (One-Time Setup)

These are the costs to move the application from a development environment to a live production state.

3.Operating & Maintenance Costs (Recurring)

Ongoing expenses are critical for ROAI as they impact the net gain over time.

QUESTION 13

You are designing end-to-end test scenarios for a business solution that uses Microsoft Dynamics 365 Sales and Dynamics 365 Finance.

You need to ensure that the business solution meets the following test requirements:

• Properly exchanges data between the Dynamics 365 apps
• Aligns with defined user workflows and business processes

Which type of testing should you use for each requirement?

To answer, drag the appropriate testing types to the correct requirements. Each testing type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Select and Place

Testing types

• Drift
• Exploratory
• Integration
• Performance
• User acceptance

Answer Area

• Properly exchanges data between the Dynamics 365 apps
• Aligns with defined user workflows and business processes

---

Box 1: Integration

Box 2: User acceptance

Box 1: Integration

Properly exchanges data between the Dynamics 365 apps

For a project involving Dynamics 365 Sales and Dynamics 365 Finance, the best testing type to verify proper data exchange is Integration Testing, specifically within a System Integration Testing (SIT) phase.

Integration Testing

This is the primary method for validating that data flows correctly between Sales (Customer Engagement) and Finance (Finance & Operations).

Purpose: Ensures seamless information flow, communication protocols, and data synchronization. Example Scenario: Creating a new Account in D365 Sales and verifying it automatically triggers the creation of a Customer in D365 Finance via Dual-write.

Box 2: User acceptance

Aligns with defined user workflows and business processes

The best testing type to ensure a Microsoft Dynamics 365 solution aligns with defined user workflows and business processes is User Acceptance Testing (UAT).

While other testing phases (like Functional or Integration) verify that the system works technically, UAT is the final "road test" where the business confirms that the solution actually supports their day-to-day operations.

QUESTION 14

A company has a Microsoft 365 tenant in Canada and multiple Microsoft Power Platform environments in Canada and the United States.

The company plans to deploy a Microsoft Copilot Studio agent to the Canadian environment that will use:

Microsoft Dataverse data stored in Canada A connector that connects to an Azure OpenAI instance in the United States

You need to ensure that the agent adheres to data residency and data movement policies before being deployed.

What should you do?

A. Ensure that the data processed by Azure OpenAI is stored in the United States.

B. From the Microsoft Purview portal, validate the Data loss prevention settings.

C. Migrate the tenant to the United States.

D. Ensure that cross-region data movement is enabled for the Canadian environment and connector dependencies.

---

Correct Answer: D

Explanation/Reference:

Explanation:

Manage Cross-Geo Data Movement Settings

Because your agent in Canada connects to Azure OpenAI in USA, data will leave your primary geography.

Explicit Opt-in:

You must navigate to the Power Platform Admin Center and explicitly allow data movement across regions for generative AI features.

Regional Scope:

If this toggle is off, Copilot features requiring the external Azure OpenAI instance will be disabled to protect residency.

Security Assurance: Microsoft does not log or retain prompt/response data during this cross-region transit for the purpose of training foundation models.

QUESTION 15

A company has a Microsoft Copilot Studio agent for customer support. You are reviewing and validating the following prompts:

• A prompt that has instructions to "help the customer as best you can"

• A prompt that helps retrieve product information from a knowledge base You need to ensure that the agent delivers consistent and accurate responses.

What should you do for each prompt? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Hot Area:

A prompt that has instructions to "help the customer as best you can":

• Add filler words to make the prompt sound more natural and conversational.
• Keep the prompt vague to enable model flexibility.
• Rewrite the prompt with clear and task-specific instructions.

A prompt that helps retrieve product information from a knowledge base:

• Add several open-ended questions to give the model broader context.
• Use responses with only reference sources and limit the response scope.
• Remove the knowledge source so that the model responds freely with general product information.

---

Box 1: Rewrite the prompt with clear and task-specific instructions.

Box 2: Use responses with only reference sources and limit the response scope.

Explanation/Reference:

Explanation:

Box 1: Rewrite the prompt with clear and task-specific instructions.

To ensure a Microsoft Copilot Studio agent delivers high-quality support, you must move beyond vague instructions like "help as best you can." Generative AI requires constraints, structured data, and persona definitions to remain consistent.

Here is how to optimize your agent for accuracy and reliability:

Refine the System Prompt A vague prompt leads to "hallucinations" (made-up facts). Replace the general instruction with a Persona and Boundary script.

Define the Persona: "You are a professional Support Specialist for [Company Name]. Your tone is empathetic, concise, and helpful."

Set Boundaries: "Only answer questions based on the provided uploaded documents. If the answer is not in the documentation, politely state you don't know and offer to connect to a human."

Establish Steps: "Always greet the user, identify their core issue, and provide a step-by-step solution."

Box 2: Use responses with only reference sources and limit the response scope.

To ensure your Microsoft Copilot Studio agent remains grounded, accurate, and avoids "hallucinations," you must configure the System Prompt to enforce strict grounding. This tells the AI to act only as a retrieval tool rather than a general-purpose assistant.

Restrict Search Scope:

In the Generative Answers node, ensure "Search only selected sources" is toggled on.

Upload specific PDFs, Manuals, or SharePoint folders rather than using the entire public web

QUESTION 16

You are designing a testing solution for Microsoft Copilot Studio agents.

You need to validate prompt engineering best practices to ensure that the agents generate accurate and contextually relevant responses.

Which prompt validation techniques and metrics should you include in the solution? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer Area

Prompt validation techniques:

• Exclude domain-specific terminology from the prompts.
• Use prompts that have varied phrasing.
• Use only simple, one-word prompts.

Metrics:

• The number of words generated per response
• Response relevance and accuracy
• The response generation time

---

Box 1: Use prompts that have varied phrasing

Box 2: Response Relevance and accuracy

Box 1: Use prompts that have varied phrasing

Here is why this technique is superior to the others for validating prompt engineering best practices: Robustness and Generalization: Using varied phrasing (synonyms, different sentence structures) tests whether the agent understands the underlying intent rather than just matching keywords. This ensures the agent is not brittle and can handle real-world user queries that vary in phrasing.

Best Practice Validation: Microsoft encourages testing agent responses by iterating and refining prompts. Testing with variations helps identify if a prompt is too rigid or if it correctly captures the context.

For a comprehensive validation strategy, this technique is typically paired with Batch Testing, where you upload a set of varied test cases to evaluate the AI's consistency and accuracy.

Incorrect:

• Exclude domain-specific terminology This is incorrect. Effective prompting often requires using domain-specific terms to ensure the AI understands the specialized context.

• Use only simple, one-word prompts This is ineffective. Simple prompts lack the context required for high-quality, accurate responses.

Box 2: Response Relevance and accuracy

By using Response Relevance and Accuracy as your primary metrics, you ensure the agent remains grounded in its knowledge sources while remaining flexible to user intent.

QUESTION 17

A company has two Microsoft Power Platform environments named Dev1 and Prod1. A Microsoft Copilot Studio agent named Agent1 is built into a solution in the Dev1 environment.

You plan to deploy Agent1 to Prod1.

You need to make Agent1 available to the users in Prod1. The solution must minimize administrative effort.

What should you do?

A. Share Agent1 with the users in Prod1.

B. Export the solution as an unmanaged solution and import the solution into Prod1.

C. Export the solution as a managed solution and import the solution into Prod1.

D. Create a new Copilot Studio agent in Prod1 by replicating the configuration of Agent1.

Correct Answer: C

Explanation/Reference:

Explanation:

To deploy a Microsoft Copilot Studio agent to a second environment while minimizing administrative work, you should use managed solutions and Power Platform Pipelines (or manual export/import if pipelines are not configured).

Follow these steps to move and share the agent effectively:

1. Prepare the Solution (Source Environment)

Since your agent is already in a solution, ensure all its dependencies are included to avoid "missing component" errors during import.

1. Export and Import

To minimize manual labor, use a Managed Solution for the target environment. Managed solutions are easier to update or remove later and prevent accidental direct edits in production.

QUESTION 18

A company has a Microsoft Power Platform environment that contains Microsoft Dataverse data.

You create a Microsoft Copilot Studio agent named Agent1 that processes the Dataverse data.

You discover that Agent1 fails to return relevant or accurate results.

You need to improve the quality and reliability of data grounding.

What should you do?

A. Retrain Agent1.

B. Verify and cleanse the Dataverse data.

C. Use an adaptive card in Agent1.

D. Add example user inputs to the training data of Agent1.

Correct Answer: B

Explanation/Reference:

To improve the reliability and accuracy of a Microsoft Copilot Studio agent grounded in Dataverse, you must focus on Dataverse data preparation, which includes cleaning, structuring, and enriching the data to ensure the agent retrieves relevant information. When Copilot fails to return accurate results, it is often due to poor data quality (garbage in, garbage out), excessive, unstructured data, or misconfigured search indexing.

QUESTION 19

A company plans to deploy a Microsoft Copilot Studio agent to enhance customer support.

The company stores customer data across ServiceNow, Microsoft Dynamics 365 Finance, Dynamics 365 Supply Chain Management, and Excel files in SharePoint Online.

You need to recommend a solution to ensure that the agent can deliver accurate and timely responses.

What should you recommend?

A. Implement a model router for query handling.

B. Create custom prompts.

C. Implement Microsoft Power Platform connectors.

D. Enable incremental indexing in Azure AI Search.

---

Correct Answer: D

Explanation/Reference:

To deploy a Microsoft Copilot Studio agent that delivers accurate responses from ServiceNow, Dynamics 365 (F&O), and SharePoint, you should centralize your data in Azure AI Search and implement incremental indexing to capture updates in real-time or on a schedule.

Immediate Solution: Enabling Incremental Indexing Incremental indexing ensures only new or modified records are processed, reducing latency and cost. High-Water Mark Detection: Configure your indexers to use a "high-water mark" policy based on a last_modified timestamp field from your sources (ServiceNow/Dynamics).

Change Tracking: For ServiceNow and Dynamics 365, use the native change tracking features in their respective connectors to signal the indexer which records have changed.

SharePoint Incremental Crawling: The Azure AI Search SharePoint indexer (currently in preview)

automatically supports incremental crawling, detecting changes in Excel files by tracking the file's metadata.

Incorrect:

[Not C] Microsoft Power Platform connectors does not cover all the data sources.

Architecture Overview Your agent will use three primary integration methods:

Knowledge Base Connectors: For high-volume unstructured data (SharePoint, ServiceNow KB).

Power Platform Connectors: For structured, real-time data (Dynamics 365, ServiceNow Incidents).

Virtual Entities: For native integration with Dynamics 365 Finance & Supply Chain.

QUESTION 20

A manufacturing company wants to deploy an agent that will automate supplier invoice processing.

You are designing a solution to evaluate the financial implications of the deployment. The company is especially concerned about budget overruns.

You need to ensure that the solution considers the total cost of ownership (TCO), the expected savings from using automation, and whether to extend the existing AI capabilities.

What should you include in the design?

A. a break-even analysis only

B. adopting prebuilt agents to reduce the deployment time

C. training a custom model

D. a return on AI investment (ROAI) analysis

---

Correct Answer: D

Explanation/Reference:

Explanation:

This design plan outlines the financial and operational framework for deploying a Microsoft-based AI agent for supplier invoice processing. By leveraging current industry benchmarks and Microsoft’s own agentic AI frameworks, this plan focuses on maximizing Return on AI Investment (ROAI) while mitigating the risk of budget overruns.

QUESTION 21

A company has a Microsoft Power Platform solution that contains the following components:

Microsoft Dataverse tables A Microsoft Power BI workspace named WS1 A canvas app named App1 that uses Dataverse A Power BI semantic model that connects to Dataverse by using DirectQuery

You plan to use generative AI to provide answers to queries based on a subset of corporate data.

You need to ensure that the data is available as a grounding data source for AI systems.

What should you do?

A. Populate a Dataverse table.

B. Share WS1.

C. Endorse the semantic model.

D. Export the semantic model.

---

Correct Answer: C

Explanation/Reference:

Explanation:

To ensure data is available as a grounding source for generative AI systems within this Power Platform solution, you should endorse the semantic model.

While populating a Dataverse table and sharing the workspace are necessary for general data accessibility, endorsing the Power BI semantic model (through certification or promotion) specifically helps generative AI systems like Power BI Copilot and Microsoft 365 Copilot prioritize and identify it as a high-quality, trusted source for grounding answers.

Why Endorsement is Key for Grounding

Generative AI systems use grounding to reduce "hallucinations" by anchoring their responses in real corporate data. In the Power BI ecosystem:

Discovery: Endorsement makes the semantic model more discoverable across the organization.

Prioritization: Copilot often prioritizes endorsed (Promoted or Certified) models when searching for relevant data to answer a natural language query.

Trust:

It signals to both the AI and the end-user that the data in this DirectQuery-connected model is verified and authoritative for business queries.

QUESTION 22

A company plans to implement an AI business solution for a consumer goods company.

You need to create agents that meet the following requirements:

Orchestrate the sales order fulfillment and shipping of goods to customers. Analyze historical data and trends to replenish stock.

Which type of agent should you use for each requirement? To answer, drag the appropriate agent types to the correct requirements. Each agent type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Select and Place

NOTE: Each correct selection is worth one point.

Agent types

• Autonomous
• Prompt-and-response
• Task

Answer Area

• Orchestrate the sales order fulfillment and shipping:
• Analyze historical data and trends:

---

Box 1: Autonomous

Box 2: Autonomous

Box 1: Autonomous

Orchestrate the sales order fulfillment and shipping of goods to customers.

An Autonomous Agent is the best choice for orchestrating sales order fulfillment and shipping in a consumer goods (CPG) environment.

While prompt-and-response agents are good for simple queries and task-based agents are good for linear workflows, an autonomous agent can manage the "many-to-many" variables inherent in supply chains without constant human intervention.

Why Autonomous is the Best Fit An autonomous agent acts as a reasoning engine rather than a static script. In fulfillment, it excels because it can:

Handle Exceptions: If a warehouse is out of a specific SKU, the agent can independently look for the next closest facility or suggest a substitute product.

Multi-Step Reasoning: It can check credit limits, verify inventory, calculate shipping dates, and trigger a logistics pickup in one cohesive flow.

Proactive Problem Solving: If a weather delay affects a shipping route, the agent can reroute the order and notify the customer before a human even spots the issue.

Box 2: Autonomous

Analyze historical data and trends to replenish stock.

For a consumer goods company managing stock replenishment, an Autonomous Agent is the best fit.

Stock replenishment requires a system that proactively monitors inventory, analyzes trends in real-time, and takes action (like drafting purchase orders) without waiting for a human to ask. While "Task" and "Prompt-and-response" agents have roles in analysis, they lack the "always-on" orchestration needed for a supply chain.

Why an Autonomous Agent Wins Proactive Replenishment Unlike prompt-based systems, an autonomous agent in Microsoft Copilot Studio can be triggered by business events—such as a low-stock alert in your ERP—rather than a user's prompt. It can:

Continuously Monitor: Watch inventory levels across multiple warehouses 24/7.

Auto-Draft Orders: Apply vendor rules and lead times to create draft purchase orders for approval.

Sense Disruptions: Adjust supply chain settings before a problem escalates based on real-time data.

QUESTION 23

A company has an AI agent that automates the review of customer feedback stored in a cloud database.

You plan to generate monthly reports from the agent's output to provide insights into customer sentiment and guide product development and marketing.

You need to ensure that the data ingested by the agent is clean and suitable for the intended use.

What should you do to prepare the data?

A. Create a workflow in Microsoft Power Automate.

B. Identify and address biased data.

C. Create an agent flow in Microsoft Copilot Studio.

D. Sort the database by customer last name.

---

Correct Answer: B

QUESTION 24

A company is designing a Microsoft Power Platform solution to reduce the manual steps of a business process by deploying an existing AI model.

You need to calculate the return on AI investment (ROAI) by identifying the metadata and telemetry of the solution.

What should you use?

A. Microsoft Power Platform admin center

B. Success by Design

C. the Business value toolkit

D. Microsoft Cloud Adoption Framework for Azure

---

Correct Answer: C

Explanation/Reference:

Explanation:

The Business Value Toolkit is the correct resource to use for calculating Return on AI Investment (ROAI) for a Microsoft Power Platform solution.

Calculating ROAI with the Business Value Toolkit The Business Value Toolkit helps organizations move beyond simple automation by providing structured templates and analytics to justify AI investments.

Metadata Identification: It captures environment-specific data, such as the number of automated flows, the type of AI models used (e.g., AI Builder), and the business units involved.

Telemetry Integration: It leverages usage data from the Power Platform admin center and Application Insights to track real-time performance, such as execution frequency and success rates.

ROI Metrics: It transforms technical telemetry into financial outcomes, such as:

• Time saved: Hours recovered from manual data entry or processing.

• Error reduction: Improvements in accuracy compared to manual steps.

• Cost avoidance: Savings from reduced reliance on specialized manual labor.

Incorrect:

[Not D] While the Cloud Adoption Framework (CAF) for Azure provides broad strategic guidance for AI adoption, the Business Value Toolkit is specifically designed to quantify the impact of low-code and AI solutions using solution metadata and telemetry.

QUESTION 25

A company has a Microsoft Power Platform environment.

You need to build two agents named Agent1 and Agent2. The solution must meet the following requirements:

Agent1 must be extendable by using the Semantic Kernel and must connect to multiple business apps and APIs.

Agent2 must connect directly to data stored in Microsoft Dataverse and must be embeddable in a Microsoft Power Apps canvas app.

What should you use to build each agent? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area

Answer Area

Agent1:

• Microsoft Foundry
• Azure Logic Apps
• Copilot in Power Apps
• Microsoft Copilot Studio

Agent2:

• Microsoft Foundry
• Azure Logic Apps
• Copilot in Power Apps
• Microsoft Copilot Studio

---

Explanation/Reference:

Box 1: Microsoft Copilot Studio

Box 2: Microsoft Copilot Studio

Explanation/Reference:

Explanation:

Box 1: Microsoft Copilot Studio

Agent1 must be extendable by using the Semantic Kernel and must connect to multiple business apps and APIs.

To build a Microsoft AI agent that integrates Semantic Kernel and connects to various business systems within the Power Platform, you will use Microsoft Copilot Studio as your primary orchestration hub.

By combining these technologies, you bridge the gap between "low-code" conversational interfaces and "pro-code" LLM orchestration. The Architecture To reach your goal, you will follow a multi-tier integration strategy: Microsoft Copilot Studio: Acts as the "Frontend" and dialog manager.

Semantic Kernel (SDK): Acts as the "Brain" hosted in an Azure function or web app.

Power Platform Connectors: Act as the "Hands" to talk to 1,200+ apps.

Custom APIs: Connected via Semantic Kernel "Plugins" or Copilot Studio "Actions."

Box 2: Microsoft Copilot Studio

Agent2 must connect directly to data stored in Microsoft Dataverse and must be embeddable in a Microsoft Power Apps canvas app.

To build a Microsoft AI agent that connects to Dataverse and is embedded in a Power Apps canvas app, you need to use Microsoft Copilot Studio as the primary development platform.

Technical Requirements To get started, ensure your environment meets these core prerequisites:

Copilot Studio Solution: Your environment must have version 2.0.0.649.1 or higher.

Dataverse Database: The environment must contain a provisioned Microsoft Dataverse database.

Admin Settings: A tenant administrator must enable "Publish Copilots with AI features" in the Power Platform admin center.

Unmanaged Customizations: Ensure that the "block unmanaged customizations" setting is disabled in your environment.

Incorrect:

• Azure Logic Apps While Logic Apps can connect to Dataverse, they are a workflow orchestration tool (similar to Power Automate) and do not provide the conversational AI interface or the embedding capabilities required for an "agent."

• Microsoft Foundry This is not a standard component of the Power Platform for building AI agents; it usually refers to internal Microsoft data management tools or unrelated external products.

• Copilot in Power Apps This refers to the AI assistant that helps makers build apps or helps users query data through a predefined side pane, but it is not the tool used to build a standalone, customizable agent that you embed yourself.

Copilot in Power Apps is an AI-powered assistant, driven by Azure OpenAI Service, that enables users to create, modify, and manage business applications using natural language instead of code. It allows developers of all skill levels to instantly build apps, design data models, and generate complex formulas by simply describing their needs in everyday language.

QUESTION 26

A company has an Azure environment that supports multiple business units.

The company plans to implement an AI solution that will perform sentiment analysis on customer product reviews.

You need to evaluate the potential cost of the solution to support return on AI investment (ROAI) analysis.

What should you use?

A. Cost Management + Billing

B. Microsoft Fabric SKU Estimator

C. Total Cost of Ownership (TCO) Calculator

D. Azure Reservations

---

Correct Answer: C

Explanation/Reference:

Explanation:

To evaluate the cost of an Azure sentiment analysis solution and support a Return on AI Investment (ROAI) analysis for multiple business units, you should use the Azure Total Cost of Ownership (TCO) Calculator.

The TCO Calculator is essential for calculating the financial impact of migrating or implementing a new solution compared to your existing infrastructure.

Step-by-Step: Using the TCO Calculator for ROAI To perform a comprehensive ROAI analysis, follow these steps to capture the full scope of ownership:

1. Define Your Current Workload Enter details about your existing infrastructure that the AI solution might replace or augment.

2. Adjust Assumptions Tailor the calculator to your business environment by adjusting key metrics.

3. Review the TCO Report The calculator generates a detailed report comparing your current costs against Azure.

QUESTION 27

You need to recommend a Microsoft Power Platform solution for customer support. The solution must include AI capabilities in Microsoft Power Automate and must meet the following requirements:

Use a centralized workspace for AI models.

Generate short overviews from large amounts of unstructured text, such as case notes or transcripts, without requiring additional training or coding.

What should you include in the recommendation for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer Area

• Use a centralized workspace:
• An Microsoft Foundry hub
• Azure OpenAI Foundry
• Microsoft Copilot Studio

• Microsoft Dataverse

• Generate short overviews:

• An AI Builder prebuilt model
• An AI Builder prebuilt prompt
• Azure OpenAI
• GitHub Copilot
• Microsoft Copilot in Power Automate

---

Box 1: Azure AI Foundry

Box 2: An AI Builder prebuilt model

Box 1: Azure AI Foundry Use a centralized workspace for AI models.

Integrating Azure AI Foundry with Microsoft Power Automate provides a powerful, centralized environment for managing the AI models that drive your customer support project. This combination allows you to leverage enterprise-grade generative AI while maintaining governance through a unified hub.

Core AI Capabilities in Power Automate Power Automate can use AI Foundry models to transform standard support flows into intelligent, context- aware processes.

Intelligent Email Responders: Automatically analyze incoming support emails to determine sentiment, urgency, and intent.

Ticket Summarization: Use GPT models to condense long customer conversation histories for human agents.

Contextual Routing: Extract key entities (like product names or order IDs) to route tickets to the correct specialized team.

Multi-Agent Orchestration: Coordinate complex support tasks—like checking a database, drafting a reply, and updating a CRM—using centralized AI logic.

Incorrect:

• Microsoft Foundry Hub While Microsoft Foundry Hubs (part of Azure AI Foundry) are used for large-scale, professional-grade AI development, AI Builder is the specific low-code tool designed to integrate seamlessly into Microsoft Power Automate.

Box 2: An AI Builder prebuilt model

Generate short overviews from large amounts of unstructured text, such as case notes or transcripts, without requiring additional training or coding.

To generate short overviews from large amounts of unstructured text in Power Automate without additional training, you should use the AI Builder "Summarize text" prebuilt model.

Key Features of the Summarize Model Zero Training Required: Works immediately out of the box with Microsoft’s pre-trained logic.

Unstructured Data: Handles case notes, long emails, and meeting transcripts effectively.

Low Code: Can be added to a Power Automate flow as a single "action" step.

Customizable Length: Allows you to specify if you want a brief summary or a more detailed overview.

QUESTION 28

A company uses Microsoft Dynamics 365 Finance for accounts payable and customer debt recovery.

You are designing an AI finance process that meets the following requirements:

Provides AI-driven details to help staff identify overdue vendor invoices and outstanding balances

Helps staff reduce how long it takes to review overdue invoices and payment history You need to recommend which Microsoft Copilot features to include in the design.

What should you recommend for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer Area

• Help identify vendor overdue invoices and outstanding balances:
• Agent management
• AI Summaries with Copilot
• The Account Reconciliation agent

• The Supplier Communication agent

• Reduce how long it takes to review overdue invoices and payment history:

• Analyze demand plans with Copilot
• Collections coordinator summary
• The Account Reconciliation agent
• The Supplier Communication agent

---

Box 1: The Account Reconciliation Agent

Box 2: Collections coordinator summary

Box 1: The Account Reconciliation Agent

Provides AI-driven details to help staff identify overdue vendor invoices and outstanding balances In Microsoft Dynamics 365 Finance, the Account Reconciliation agent and Copilot for Finance provide a powerful AI-driven ecosystem to manage overdue vendor invoices and customer debt recovery. These agents shift your team from reactive manual checking to proactive, exception-based management.

The Account Reconciliation Agent This agent automates the high-volume task of matching subledger transactions to the general ledger, specifically for Accounts Payable (AP) and Accounts Receivable (AR).

Automated Matching: Continuously monitors and reconciles transactions throughout the month rather than waiting for period-end.

Exception Identification: Automatically flags discrepancies, such as voucher amount mismatches or unmatched entries, for staff review.

AI-Suggested Actions: Using Microsoft Copilot, the agent suggests the most likely resolution for each exception, such as posting a correction or reaching out to a vendor.

Efficiency: Reduces the time spent on manual spreadsheet-based reconciliations, allowing staff to focus on resolving the "why" behind overdue balances

Box 2: Collections coordinator summary

Helps staff reduce how long it takes to review overdue invoices and payment history

To reduce the time spent reviewing overdue invoices and payment history in Microsoft Dynamics 365 Finance, you need the Collections Coordinator Summary feature powered by Copilot.

This AI-driven process automates the synthesis of customer financial data, allowing staff to move directly from review to action without manual data digging.

QUESTION 29

A company has an AI agent that automates the review of customer feedback stored in a cloud database.

You plan to generate monthly reports from the agent's output to provide insights into customer sentiment and guide product development and marketing.

You need to ensure that the data ingested by the agent is clean and suitable for the intended use.

What should you do to prepare the data?

A. Ensure that the size of the database does not exceed 100 GB.

B. Translate the data into a single language.

C. Identify and address biased data.

D. Sort the database by customer last name.

---

Correct Answer: C

Explanation/Reference:

Explanation:

Correct:

• Identify and address biased data.

To ensure that the customer feedback ingested by your Microsoft AI agent is clean and suitable for monthly sentiment reports, the most effective action is to identify and address biased data.Data bias in sentiment analysis can lead to skewed reports that misrepresent customer satisfaction or ignore the needs of specific demographic groups.‘

Incorrect:

• Create a workflow in Microsoft Power Automate

• Create an agent flow in Microsoft Copilot Studio.

• Ensure that the size of the database does not exceed 100 GB.

• Sort the database by customer last name.

QUESTION 30

A company has an Azure environment that supports multiple business units.

The company plans to implement an AI solution that will perform sentiment analysis on customer product reviews.

You need to evaluate the potential cost of the solution to support return on AI investment (ROAI) analysis.

What should you use?

A. Total Cost of Ownership (TCO) Calculator

B. Azure Reservations

C. Azure pricing calculator

D. Azure Monitor

---

Correct Answer: C

Explanation/Reference:

Explanation:

Correct:

Azure pricing calculator (Best choice) The best tool to evaluate the potential cost of a new AI solution to support ROI analysis is the Azure pricing calculator.

Why Azure Pricing Calculator is BestProactive Estimation: It is specifically designed to estimate the costs of Azure services before they are deployed.

Granular Planning: It allows you to select specific services (e.g., Azure AI Language, Cognitive Services, Azure Machine Learning), define usage patterns, regions, and tiers to create a detailed cost estimate.

Scenario Comparison: You can create different scenarios (e.g., comparing different language models or usage volumes) to estimate the impact on ROAI

Comparison of Tools Azure Pricing Calculator: Estimates costs for new, un-deployed projects. (Best Choice).

Total Cost of Ownership (TCO) Calculator: Compares on-premises infrastructure costs against Azure, typically used for large-scale migration strategies, not specific AI service modeling.

Cost Management + Billing: Monitors and analyzes actual, real-time spending on already deployed resources.

For a complex AI solution involving.

• Total Cost of Ownership (TCO) Calculator (Second best choice)

While Cost Management + Billing is essential for tracking actual spend once a solution is running, the TCO Calculator is specifically designed for the pre-implementation phase to support Return on AI Investment (ROAI) analysis.

It allows you to estimate and compare the potential costs of moving a workload to Azure —including labor, networking, and storage—against an existing process or alternative solution.

• Cost Management + Billing (Third best)

Azure pricing calculator and Total Cost of Ownership (TCO) Calculator are both better than Cost Management + Billing, as they evaluate the potential cost and support a Return on AI Investment (ROAI) analysis before the solution is built, you need to estimate future expenses based on expected usage.

Cost Management + Billing does post-deployment tracking.

A good tool still for this scenario is Cost Management + Billing. Cost Management + Billing allows you to break down and evaluate costs across many business units using tags and scope filtering. This granular data is essential for calculating the Return on AI Investment (ROAI) for specific departments or the entire organization.

Incorrect

• Azure Monitor
• Azure Reservations
• Azure savings plans

Is used to reduce costs for compute services via long-term commitment.

It is a way to lower your bill, but not a tool for evaluating or reporting on investment performance.

• Microsoft Fabric SKU Estimator

Is used to estimate capacity needs for Fabric-specific data projects. It is eseful only if your sentiment analysis solution is built specifically on the Microsoft Fabric platform.

• Azure pricing calculator

To evaluate the potential cost of an AI solution for sentiment analysis on Azure, you should use the Azure Pricing Calculator.This tool allows you to estimate the monthly and annual costs of the specific services required for your solution—such as Azure AI Language (which provides sentiment analysis) or Azure OpenAI Service—based on your expected volume of feedback data.

• Total Cost of Ownership (TCO) Calculator

To evaluate the cost of an Azure sentiment analysis solution and support a Return on AI Investment (ROAI) analysis for multiple business units, you should use the Azure Total Cost of Ownership (TCO) Calculator.

The TCO Calculator is essential for calculating the financial impact of migrating or implementing a new solution compared to your existing infrastructure.

Step-by-Step: Using the TCO Calculator for ROAI

To perform a comprehensive ROAI analysis, follow these steps to capture the full scope of ownership:

1. Define Your Current Workload

Enter details about your existing infrastructure that the AI solution might replace or augment.

1. Adjust Assumptions

Tailor the calculator to your business environment by adjusting key metrics.

1. Review the TCO Report

The calculator generates a detailed report comparing your current costs against Azure.

QUESTION 31

A company has an Azure environment that supports multiple business units.

The company plans to implement an AI solution that will perform sentiment analysis on customer product reviews.

You need to evaluate the potential cost of the solution to support return on AI investment (ROAI) analysis.

What should you use?

A. Azure savings plans

B. Microsoft Fabric SKU Estimator

C. Cost Management + Billing

D. Azure Monitor

---

Correct Answer: C

Explanation/Reference:

Correct:

• Azure pricing calculator (Best choice) The best tool to evaluate the potential cost of a new AI solution to support ROI analysis is the Azure pricing calculator.

Why Azure Pricing Calculator is BestProactive Estimation: It is specifically designed to estimate the costs of Azure services before they are deployed.

Granular Planning: It allows you to select specific services (e.g., Azure AI Language, Cognitive Services, Azure Machine Learning), define usage patterns, regions, and tiers to create a detailed cost estimate.

Scenario Comparison: You can create different scenarios (e.g., comparing different language models or usage volumes) to estimate the impact on ROAI

Comparison of Tools Azure Pricing Calculator: Estimates costs for new, un-deployed projects. (Best Choice).

Total Cost of Ownership (TCO) Calculator: Compares on-premises infrastructure costs against Azure, typically used for large-scale migration strategies, not specific AI service modeling.Cost Management + Billing: Monitors and analyzes actual, real-time spending on already deployed resources. For a complex AI solution involvin

• Total Cost of Ownership (TCO) Calculator (Second best choice) While Cost Management + Billing is essential for tracking actual spend once a solution is running, the TCO Calculator is specifically designed for the pre-implementation phase to support Return on AI Investment (ROAI) analysis. It allows you to estimate and compare the potential costs of moving a workload to Azure —including labor, networking, and storage—against an existing process or alternative solution.

• Cost Management + Billing (Third best) Azure pricing calculator and Total Cost of Ownership (TCO) Calculator are both better than Cost Management + Billing, as they evaluate the potential cost and support a Return on AI Investment (ROAI) analysis before the solution is built, you need to estimate future expenses based on expected usage. Cost Management + Billing does post-deployment tracking.

A good tool still for this scenario is Cost Management + Billing. Cost Management + Billing allows you to break down and evaluate costs across many business units using tags and scope filtering.

This granular data is essential for calculating the the Return on AI Investment (ROAI) for specific departments or the entire organization.

Incorrect:

• Azure Monitor
• Azure Reservations
• Azure savings plans

Is used to reduce costs for compute services via long-term commitment.

It is a way to lower your bill, but not a tool for evaluating or reporting on investment performance

• Microsoft Fabric SKU Estimator

Is used to estimate capacity needs for Fabric-specific data projects. It is eseful only if your sentiment analysis solution is built specifically on the Microsoft Fabric platform

Note:

• Azure pricing calculator

To evaluate the potential cost of an AI solution for sentiment analysis on Azure, you should use the Azure Pricing Calculator.This tool allows you to estimate the monthly and annual costs of the specific services required for your solution—such as Azure AI Language (which provides sentiment analysis) or Azure OpenAI Service—based on your expected volume of feedback data.

• Total Cost of Ownership

(TCO) Calculator To evaluate the cost of an Azure sentiment analysis solution and support a Return on AI Investment (ROAI) analysis for multiple business units, you should use the Azure Total Cost of Ownership (TCO) Calculator.

The TCO Calculator is essential for calculating the financial impact of migrating or implementing a new solution compared to your existing infrastructure.

Step-by-Step: Using the TCO Calculator for ROAI

To perform a comprehensive ROAI analysis, follow these steps to capture the full scope of ownership:

1. Define Your Current Workload

Enter details about your existing infrastructure that the AI solution might replace or augment.

1. Adjust Assumptions

Tailor the calculator to your business environment by adjusting key metrics.

1. Review the TCO Report

The calculator generates a detailed report comparing your current costs against Azure.

QUESTION 32

A company has an Azure environment that supports multiple business units.

The company plans to implement an AI solution that will perform sentiment analysis on customer product reviews.

You need to evaluate the potential cost of the solution to support return on AI investment (ROAI) analysis.

What should you use?

A. Azure Reservations

B. Microsoft Fabric SKU Estimator

C. Anomaly Detection in Azure Cost Management

D. Azure pricing calculator

---

Correct Answer: D

Explanation:

• Azure pricing calculator (Best choice)

The best tool to evaluate the potential cost of a new AI solution to support ROI analysis is the Azure pricing calculator.

Why Azure Pricing Calculator is BestProactive Estimation: It is specifically designed to estimate the costs of Azure services before they are deployed.

Granular Planning: It allows you to select specific services (e.g., Azure AI Language, Cognitive Services, Azure Machine Learning), define usage patterns, regions, and tiers to create a detailed cost estimate.

Scenario Comparison: You can create different scenarios (e.g., comparing different language models or usage volumes) to estimate the impact on ROAI

Comparison of Tools Azure Pricing Calculator: Estimates costs for new, un-deployed projects. (Best Choice）

Total Cost of Ownership (TCO) Calculator: Compares on-premises infrastructure costs against Azure, typically used for large-scale migration strategies, not specific AI service modeling.Cost Management + Billing: Monitors and analyzes actual, real-time spending on already deployed resources. For a complex AI solution involvin

• Total Cost of Ownership (TCO) Calculator (Second best choice)

While Cost Management + Billing is essential for tracking actual spend once a solution is running, the TCO Calculator is specifically designed for the pre-implementation phase to support Return on AI Investment (ROAI) analysis. It allows you to estimate and compare the potential costs of moving a workload to Azure —including labor, networking, and storage—against an existing process or alternative solution.

• Cost Management + Billing (Third best)

Azure pricing calculator and Total Cost of Ownership (TCO) Calculator are both better than Cost Management + Billing, as they evaluate the potential cost and support a Return on AI Investment (ROAI) analysis before the solution is built, you need to estimate future expenses based on expected usage. Cost Management + Billing does post-deployment tracking.

A good tool still for this scenario is Cost Management + Billing. Cost Management + Billing allows you to break down and evaluate costs across many business units using tags and scope filtering. This granular data is essential for calculating the Return on AI Investment (ROAI) for specific departments or the entire organization.

Incorrect:

• Azure Monitor
• Azure Reservations
• Azure savings plans

Is used to reduce costs for compute services via long-term commitment. It is a way to lower your bill, but not a tool for evaluating or reporting on investment performance.

• Microsoft Fabric SKU Estimator

Is used to estimate capacity needs for Fabric-specific data projects. It is eseful only if your sentiment analysis solution is built specifically on the Microsoft Fabric platform.

Note:

• Azure pricing calculator

To evaluate the potential cost of an AI solution for sentiment analysis on Azure, you should use the Azure Pricing Calculator.This tool allows you to estimate the monthly and annual costs of the specific services required for your solution—such as Azure AI Language (which provides sentiment analysis) or Azure OpenAI Service—based on your expected volume of feedback data.

• Total Cost of Ownership (TCO) Calculator

To evaluate the cost of an Azure sentiment analysis solution and support a Return on AI Investment (ROAI) analysis for multiple business units, you should use the Azure Total Cost of Ownership (TCO) Calculator.

The TCO Calculator is essential for calculating the financial impact of migrating or implementing a new solution compared to your existing infrastructure.

Step-by-Step: Using the TCO Calculator for ROAI To perform a comprehensive ROAI analysis, follow these steps to capture the full scope of ownership:

1. Define Your Current Workload Enter details about your existing infrastructure that the AI solution might replace or augment.

2. Adjust Assumptions Tailor the calculator to your business environment by adjusting key metrics.

3. Review the TCO Report The calculator generates a detailed report comparing your current costs against Azure.

Design AI-powered business solutions

Testlet 1

Overview Contoso, Ltd. is a high-tech manufacturing company that uses Microsoft Dynamics 365 Finance. Dynamics 365 Supply Chain Management, and Dynamics 365 Commerce for its North American operations. The company designs and develops innovative products that have many patents and proprietary technologies. The patents and engineering designs are closely guarded secrets.

Contoso executives want to integrate and adopt AI solutions to help scale the company in preparation for an anticipated period of rapid growth.

The company has multiple legal entities and Azure subscriptions that will be used in the adopted AI solutions.

Requirements AI Adoption The following executives will have specific responsibilities in the overall AI adoption:

• Chief Technology Officer (CTO): Select one Dynamics 365 Finance, Dynamics 365 Supply Chain Management or Dynamics 365 Commerce prebuilt AI agent and one custom Microsoft Copilot Studio AI agent to prioritize and deploy during the initial AI adoption phase.
• Chief Information Officer (CIO): Ensure that appropriate security labels are assigned to the data used by the AI agents.
• Chief Financial Officer (CFO): Analyze the return on investment (ROI) for the AI agents being deployed. Chief Information Security Officer (CISO): Discover and inventory AI resources for auditing.
• Chief Executive Officer (CEO): Ensure that all solutions adhere to industry-standard responsible AI practices.

All AI initiatives and agents will have a detailed business use case, a defined audience profile, and an estimated ROI that will compare the cost savings of the current process against the estimated costs of using the new AI solutions.

The company's research and development (R&D) department already has a custom Model Context Protocol (MCP) server that contains comprehensive product specifications and compliance data.

Prebuilt AI Agent

The CTO has NOT yet selected which prebuilt AI agent to use in Dynamics 365 Supply Chain Management. The CTO wants to view available agent templates to identify which agent will add the most business value.

Depending on which high-priority AI agents are identified, its agent capabilities must be previewed in a discovery meeting with the relevant business operation stakeholders.

Custom AI Agent

Contoso has identified the following custom AI agent requirements:

• The custom AI agent will use data from Dynamics 365 Supply Chain Management to answer questions for the manufacturing team as a low-code solution.

• The custom AI agent will be accessible from within Microsoft Teams.

• The custom AI agent must be designed to eventually connect to other agents that can be selected based on their description.

• The topics used in the custom AI agent will be selected based NOT on a trigger phrase, but on a description of the purpose of the query, to make the interactions more conversational.

• The custom AI agent must be able to answer questions about product specifications by using existing technologies. The product specifications are maintained by the R&D department.

• The custom AI agent must be integrated with and accessible from Dynamics 365 Supply Chain Management.

• The custom AI agent must be able to use Dynamics 365 Supply Chain Management business logic that is stored outside of the application.

Analysis, Reporting, and Troubleshooting

Analysis, Reporting, and Troubleshooting

Contoso has identified the following analysis, reporting, and troubleshooting requirements:

• The CISO will audit all the AI solutions monthly for compliance and security.

• The CFO will analyze all the AI solutions quarterly to compare the estimated ROI against actual measured efficiencies and adoption. The CFO will use the Copilot Studio agent usage estimator to perform this analysis.

• The CISO wants to identify how much sensitive data was accessed for a given AI agent run and who accessed the data. Too much sensitive data accessed by a single user might indicate a high security risk.

• The CTO wants to track user feedback on the quality of the AI agent responses during user interactions with the agents. Consistently poor feedback will trigger an escalated reengineering discussion.

• The CEO wants a quarterly assessment of all the required metrics for their specific responsibilities. The tools used for the assessments must be Microsoft-recommended and must verify reliability, interpretability, fairness, and compliance.

• The CFO wants to identify how many interactions with the AI agents are abandoned on a given day as compared to resolved conversations. Too many abandoned sessions might indicate that Copilot Studio credits are being used inefficiently by end users.

QUESTION 1

What should you recommend to assist the CTO with the prebuilt agent selection process?

A. Agent management

B. Copilot Studio

C. Lifecycle Services (LCS)

D. Immersive Home

---

Correct Answer: A Section: (none)

Explanation/Reference:

Explanation:

Agent management is the correct tool to use for viewing available agent templates and deciding which AI agent to use within Dynamics 365 Supply Chain Management.

Available Agent Discovery Tools When working within Dynamics 365 Finance and Operations apps (including Supply Chain Management), the specifically designed interface for these tasks is Agent management.

Agent Management: A dedicated preview feature in Finance and Operations apps that allows users to discover, configure, and manage autonomous AI-powered agents.

Incorrect:

[Not B] Copilot Studio: While this is the platform used to build and customize agents and track detailed analytics (like thumbs-up/down feedback), it is a standalone low-code tool rather than the primary discovery pane inside the SCM interface.

[Not C] Lifecycle Services (LCS): Primarily used for environment management, deployments, and updates rather than the day-to-day discovery of specific AI agent templates.

[Not D] Immersive Home: Typically refers to a broader Microsoft 365 or entry-level experience, not the specialized ERP agent management portal.

Scenario:

Prebuilt AI Agent

The CTO has NOT yet selected which prebuilt AI agent to use in Dynamics 365 Supply Chain Management. The CTO wants to view available agent templates to identify which agent will add the most business value.

The CTO wants to track user feedback on the quality of the AI agent responses during user interactions with the agents. Consistently poor feedback will trigger an escalated reengineering discussion.

QUESTION 2

What should you include in the custom AI agent design to meet the R&D product specifications and the compliance information requirements? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer Area

To expose the data to the agent, create:

• an Azure AI Bot Service channel
• a custom connector
• a custom OData entity
• the Semantic Kernel

Add to the agent:

• an event trigger
• the MCP server
• a REST API
• a tool

---

Box 1: Custom connector

Box 2: a tool

Explanation/Reference:

Explanation:

Scenario:

The company's research and development (R&D) department already has a custom Model Context Protocol (MCP) server that contains comprehensive product specifications and compliance data.

The custom AI agent must be able to answer questions about product specifications by using existing technologies. The product specifications are maintained by the R&D department.

Box 1: Custom connector To expose the data to the agent, create

To expose data from a custom Model Context Protocol (MCP) server to a Microsoft Dynamics 365 AI agent (built in Copilot Studio) to answer questions about product specifications, you should create a Custom Connector.

This custom connector acts as the bridge between the custom MCP server and Power Platform/Copilot Studio, enabling the agent to consume the data and tools provided by the MCP server.

Box 2: a tool Add to the agent

To add a custom Model Context Protocol (MCP) server that contains comprehensive product specifications and compliance data to a Microsoft Dynamics 365 AI agent, you should use Microsoft Copilot Studio and configure the MCP server as a tool (or skill) within the agent.

Here are the specific steps and components to use:

Platform: Use Microsoft Copilot Studio to create or update the custom agent.

*-> Method: In the agent configuration, go to the Tools section and select Add a tool > Model Context Protocol (MCP).

MCP Server Details: Input the required technical details for your custom server, including the Server Name, Description, and Server URL.

Authentication: Configure the necessary authentication type (e.g., OAuth 2.0 or API Key) as required by your custom MCP server to ensure secure access to product specifications and compliance data.

*-> Tool Binding: The MCP server will expose the specifications as tools that the agent can "call" at runtime to answer user questions about products.

Testlet 2

**Background **

Fabrikam, Inc., is a global consumer goods company that is undergoing a digital transformation initiative to migrate its entire infrastructure to the Microsoft cloud. As a key element of this cloud migration, the company will implement Microsoft Dynamics 365 Sales, moving away from the current on-premises proprietary technologies used by its business-to-business (B2B) sales team.

As part of the cloud migration, Fabrikam will adopt an AI-first approach to its business solutions and implement AI solutions, wherever possible, to streamline operations.

Problem Statements

Fabrikam's infrastructure currently relies on various on-premises systems that require sales executives to use corporate computers with physical keyboards to access business information during customer interactions. Mobile phones cannot be used for these purposes, as the systems depend on keyboard input. As a result, the sales executives spend a lot of time using keyboards to search for data on several disparate systems and file servers, rather than focusing on the customers. This affects the customer experience.

Fabrikam stakeholders are concerned that users will be hesitant to adopt AI. If the AI initiatives are NOT adopted, cost savings will never be realized. Additionally, funding for future AI initiatives will depend on demonstrating an increase in AI adoption month over month. As the AI agent initiative for the sales team will be the first for Fabrikam, the rapid adoption of the agent is a high priority.

Planned Initiatives

General Fabrikam management has prioritized AI-driven projects to improve efficiency, customer engagement, and responsible AI adoption. The current application infrastructure is on-premises and must be migrated to the cloud to support the adoption of these technologies.

Infrastructure Migration

Fabrikam plans to migrate from its current on-premises infrastructure to a completely cloud-based topology; this will include user authentication, the security framework, and, primarily, the adoption of the services by end users.

All the data from the different systems will be consolidated into a single data source - a common data model that will use a Microsoft Dataverse environment as a single source of truth (SSOT) for the sales team.

Sales Cycle Enablement

• To achieve the company's objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle:

• Use low-code development to create a single AI agent that has Dataverse as its core component. Ensure that sales managers can access unanswered correspondence from prospects and intervene as appropriate.

• Replace the previous proprietary software with Dynamics 365 Sales to track sales cycles and customer interactions.

• Have the sales executives use Dynamics 365 Sales to track interactions for open opportunities and send follow-up communications to prospects.

• Have the sales executives use handsfree headsets to interact with an AI agent when they have questions about internal policies or customer data.

Requirements

Infrastructure Migration

Fabrikam has identified the following infrastructure migration requirements:

Azure must be used for all future infrastructure workloads.

The company must follow Microsoft-recommended methodologies for infrastructure migration to the cloud.

Any created AI agents must have their return on investment (ROI) calculated to ensure that the solution will save the company money.

Sales Cycle Enablement

• Fabrikam has identified the following requirements for sales cycle enablement:

• The final AI agent must follow Microsoft recommendations for a conversational user experience.

• A designated checklist must be reviewed to ensure that the AI agent follows Microsoft deployment recommendations for a compliant solution.

• Detailed telemetry must be logged for the first created AI agent to help troubleshoot and optimize the agent during the initial AI agent adoption process.

• Unexpected AI agent actions must end in an escalation to a live representative. For example, a sales executive must be rerouted to a representative if the agent cannot answer a question after two failed attempts.

• The return on investment (ROI) of switching from the current process to the future process is required for stakeholder sign off.

• The sales team must use Dynamics 365 Sales to correspond with prospects more quickly and efficiently than currently.

• Sales managers must report on the adoption of the AI agent to key Fabrikam stakeholders on a monthly basis.

• Any sensitive information, such as user IDs and names, shared via the AI agent must be tracked for future auditing.

QUESTION 1

Which template should you use for the AI agent to meet the requirements for the sales executives?

A. IT Helpdesk in Microsoft Copilot Studio

B. AI agents in Microsoft Foundry

C. Voice in Microsoft Copilot Studio

D. AI chat in Microsoft Foundry

---

Correct Answer: C

Sales Cycle Enablement To achieve the company's objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle:

Have the sales executives use Dynamics 365 Sales to track interactions for open opportunities and send follow-up communications to prospects.

*-> Have the sales executives use handsfree headsets to interact with an AI agent when they have questions about internal policies or customer data.

To enable handsfree headset interaction with an AI agent for internal policies and customer data in Dynamics 365 Sales, you should use Microsoft Copilot Studio to create a custom agent template.

Here is the breakdown of the recommended approach and templates:

Recommended Template Voice-enabled agent template (in Copilot Studio): This template provides the foundational, pre-configured setup for Interactive Voice Response (IVR) capabilities, allowing for natural language voice inputs and text-to-speech output.

Internal Data Knowledge Source: Within this agent, you will connect to Dataverse (for customer data) and configure Knowledge Sources (for internal policy documents).

Note:

To implement a hands-free AI agent for Dynamics 365 Sales using the Voice agent template in Microsoft Copilot Studio, follow these steps to enable voice-first interactions for internal policies and customer data.

1. Create a Voice-Enabled Agent

2. Configure Hands-Free Interaction

3. Connect to Internal Dat

QUESTION 2

Which tool should you use for the prospect communication requirements in Dynamics 365 Sales?

A. Azure AI Search

B. Copilot email assist

C. the Voice template Microsoft Copilot Studio

D. Deep Research in Microsoft Foundry Agent Service

---

Correct Answer: B

Explanation:

Scenario:

Requirements

*-> The sales team must use Dynamics 365 Sales to correspond with prospects more quickly and efficiently than currently.

Sales Cycle Enablement

To achieve the company's objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle:

Ensure that sales managers can access unanswered correspondence from prospects and intervene as appropriate.

Have the sales executives use Dynamics 365 Sales to track interactions for open opportunities and send follow-up communications to prospects

---

In Dynamics 365 Sales, the Copilot email assist feature acts as a powerful accelerator for handling prospects by automating the most time-consuming parts of communication.

Here is how it helps you move faster and more efficiently:

Instant Drafting: You can generate professional-looking email drafts in seconds by choosing a predefined category (like "reply to an inquiry" or "follow up") or by entering your own custom prompt.

Context-Aware Personalization: The AI uses data directly from your CRM—such as past interactions, deal status, and customer notes—to ensure every message is tailored specifically to that prospect's needs. Tone & Style Adjustments: You can quickly refine the length and tone (e.g., formal, friendly, or urgent) of a draft to better resonate with a particular recipient.

Summarization: When dealing with long email chains, Copilot provides a concise summary of the conversation history, allowing you to catch up instantly without reading through every old message. Actionable Reminders: It monitors your inbox to identify pending action items or key customer requests you may have missed, ensuring no prospect falls through the cracks.

Seamless Integration: These tools are available directly within the Dynamics 365 Email Rich Text Editor and across Microsoft 365 apps like Outlook and Teams, keeping you in your flow of work.

QUESTION 3

Which components should you use to meet the sales cycle enablement requirements? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer Area

For Al agent creation:

• Microsoft Foundry

• Dynamics 365 Sales

• Microsoft Copilot Studio

• the Power Platform admin center

For unexpected Al agent actions:

• a custom connector

• an event trigger

• a Fallback topic

• a REST API

---

Explanation/Reference:

Box 1: Microsoft Copilot Studio

Box 2: a Fallback topic

Box 1: Microsoft Copilot Studio For AI agent creation

Scenario:

A designated checklist must be reviewed to ensure that the AI agent follows Microsoft deployment recommendations for a compliant solution.

The Microsoft tool that should be used to create the AI agent is Microsoft Copilot Studio.

It is a low-code platform specifically designed for building and managing intelligent agents that integrate with Microsoft Dataverse as a core component for storing data and providing business context. To ensure the agent follows Microsoft's deployment recommendations, users should consult the implementation checklist provided within the Microsoft Copilot Studio documentation.

Key Features of Microsoft Copilot Studio:

Low-Code Interface: Uses a graphical builder or natural language to design agent behaviors and conversation flows.

Dataverse Integration: Leverages Dataverse as the enterprise data platform to ground agents in organizational knowledge and store shared context.

Governance and Compliance: Includes built-in responsible AI features and aligns with enterprise security standards.

Multi-Channel Deployment: Allows publishing agents across Microsoft Teams, websites, and mobile app

Box 2: a Fallback topic

For unexpected AI agent actions.

Scenario:

Unexpected AI agent actions must end in an escalation to a live representative. For example, a sales executive must be rerouted to a representative if the agent cannot answer a question after two failed attempts.

In a low-code environment using Microsoft Copilot Studio with Dataverse, you can ensure unexpected AI actions lead to a live representative by configuring specific system topics.

1. Configure the System Fallback Topic

The Fallback system topic triggers when the AI agent cannot match a user's intent to any existing topic or knowledge source with sufficient confidence.

Enable Fallback: In Copilot Studio, navigate to Settings > General Settings > System fallback and click Add.

Action: Edit the Fallback topic to include a Go to topic node that redirects to the Escalate system topic.

1. Implement the Escalate System Topic The Escalate topic is the primary mechanism for handoffs.

2. Handle Errors and Infinite Loops

Question Set 3 - Design AI-powered business solutions

QUESTION 1

You need to design a Microsoft 365 Copilot solution to optimize employee productivity. The solution must meet the following requirements:

Ensure that the employees can query content stored in a subset of Microsoft SharePoint Online sites and in Teams by using natural language-based prompt actions.

Ensure that employees receive contextually relevant responses in Microsoft 365 Copilot.

What should you include in the design?

A. Build a Microsoft Power Automate desktop flow to read the SharePoint content and post the responses to Teams.

B. Modify SharePoint settings.

C. Create a custom REST API that crawls the SharePoint content.

D. Configure Microsoft Graph access

---

Correct Answer: D

Explanation/Reference:

Explanation:

To enable Microsoft 365 Copilot to query a specific subset of SharePoint Online and Teams content using natural language, you can implement a combination of Restricted SharePoint Search and Microsoft Graph Connectors.

1. Restricting Content Access You can limit the scope of data Copilot searches by using features that control which sites are indexed or accessible.

2. Configuring Microsoft Graph Access Microsoft Graph acts as the bridge connecting Copilot to your organizational data. To integrate specific sources.

3. Enabling Prompt Actions & Context Declarative Agents: You can create specialized Copilot Agents grounded in specific SharePoint knowledge sources. These agents use natural language instructions to focus on a subset of data for more contextually relevant responses.

Direct Referencing: Users can improve response relevance by explicitly naming files, folders, or Teams channels in their natural language prompts (e.g., "Summarize notes from the 'Product Launch' channel").

QUESTION 2

A company uses Microsoft Dynamics 365 Finance to manage accounts payable.

You are designing an AI invoice processing solution.

You need to recommend the prerequisites to configure a prebuilt copilot for accounts payable.

What should you recommend?

A. From Microsoft Copilot Studio, create an accounts payable agent.

B. Extend Microsoft 365 Copilot for Sales to an accounts payable agent.

C. Build an AI tool in Microsoft Foundry.

D. From the Power Platform admin center, assign the Finance and Operations AI security role to users.

---

QUESTION 2 A company uses Microsoft Dynamics 365 Finance to manage accounts payable.

You are designing an AI invoice processing solution.

You need to recommend the prerequisites to configure a prebuilt copilot for accounts payable.

What should you recommend?

A. From Microsoft Copilot Studio, create an accounts payable agent.

B. Extend Microsoft 365 Copilot for Sales to an accounts payable agent.

C. Build an AI tool in Microsoft Foundry.

D. From the Power Platform admin center, assign the Finance and Operations AI security role to users.

---

Explanation/Reference:

Users must be assigned the Finance and Operations AI and AIB Roles in the Dataverse environment.

Note:

To configure the prebuilt Copilot for Accounts Payable in Microsoft Dynamics 365 Finance, you must satisfy several foundational and technical requirements.

1. System & Environment Prerequisites

2. Technical Configuration & Data Settings

3. Licensing & Security Roles Licenses

*-> Dataverse Roles: Users must be assigned the Finance and Operations AI and AIB Roles in the Dataverse environment.

1. Feature Activation

QUESTION 3

A company plans to deploy a Microsoft Dynamics 365 Contact Center agent.

You need to ensure that the agent can transfer the conversation to a live customer service representative.

Which two components should you include in the solution? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Microsoft Foundry

B. Microsoft Copilot Studio

C. Microsoft 365 Agents Toolkit

D. an Azure AI Bot Service skill

E. Customer engagement hub

---

Correct Answer: BE

Explanation/Reference:

To implement a Microsoft Dynamics 365 Contact Center solution that enables seamless handoff between a virtual agent and a live representative, you must integrate Microsoft Copilot Studio with the Customer Engagement Hub (typically Dynamics 365 Customer Service or Omnichannel).

Core Components & Setup

1. Copilot Studio Configuration:

Connect to Engagement Hub: In Copilot Studio, navigate to Settings > Customer Engagement Hub and select Dynamics 365 Customer Service.

Enable Agent Transfer: Under the Channels tab, select the Dynamics 365 Customer Service tile and click Connect. This establishes the link between the bot and your live agent environment.

Configure Handoff Topic: Modify the Escalate system topic or create a custom topic. Use the Transfer conversation node to trigger the move to a live representative. You can include a private message to the agent to provide context.

1. Customer Engagement Hub (Dynamics 365) Setup:

Workstream Integration: In the Customer Service Admin Center, create or open a workstream (e.g., for Live Chat or Voice). Add your Copilot Studio agent to this workstream to ensure it is the first point of contact.

Routing Rules: Define rules to route the escalated conversation to the correct live agent queue based on context variables passed from the bot.

1. Handoff Experience:

Context Sharing: When a transfer occurs, the live representative receives the full conversation transcript and any variables collected by the bot, allowing them to resume the interaction without asking the customer to repeat information.

Agent Workspace: Live agents accept the transfer through the Customer Service Workspace or Omnichannel for Customer Service.

QUESTION 4

、A company uses Microsoft Dynamics 365 Supply Chain Management.

You are designing an AI supply chain process that meets the following requirements:

Provides managers with AI-driven insights that surface key information from customer orders

Helps planners use AI to anticipate future product needs more accurately You need to recommend which Microsoft Copilot features to include in the design.

What should you recommend for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

NOTE: Each correct selection is worth one point.

Answer Area

Provide AI-driven insights from customer orders:

• Al Summaries with Copilot
• Generative insights for Demand planning
• The Customer credit and collections workspace
• Workload insights with Copilot

Anticipate future product needs:

• Generative insights for Demand planning
• Microsoft Power BI
• Product information management
• The Supplier Communications Agent

---

Box 1: AI summaries with Copilot

Box 2: Generative insights for Demand planning

Box 1: AI summaries with Copilot

Provides managers with AI-driven insights that surface key information from customer orders

To provide managers with AI-driven insights from customer orders in Dynamics 365 Supply Chain Management, use the AI summaries with Copilot feature, specifically leveraging the embedded Customer Summary capabilities. This tool provides instant, personalized overviews of critical data, such as backordered items, credit limits, and risk indicators, directly within the workspace.

Box 2: Generative insights for Demand planning

Helps planners use AI to anticipate future product needs more accurately

The Copilot Generative insights for Demand planning feature in Microsoft Dynamics 365 Supply Chain Management enables demand planners to move from reactive, manual forecasting to proactive, AI-driven demand anticipation. By analyzing, clustering, and interpreting vast datasets, Copilot helps identify patterns such as seasonality and signal correlations to improve accuracy.

QUESTION 5

A company has a Microsoft 365 E5 subscription and uses Microsoft Copilot Studio.

The company has a Microsoft SharePoint Online library that contains 10,000 policy PDFs from various departments. The library contains a populated column named Department for each PDF.

You need to design a Copilot Studio agent that will use the SharePoint library as a knowledge source. The solution must meet the following requirements:

• Enable the agent to answer user questions about company policies.

• Ensure that the agent can identify which departments and policies are connected.

What should you include in the design for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Enable the agent to answer questions about company policies:

• Build a custom model in Microsoft Foundry.
• From Copilot Studio, add SharePoint as a knowledge source.
• Import the PDFs into Microsoft Dataverse.
• Use AI Builder to process and feed SharePoint content.

Identify which departments and policies are connected:

• Apply Microsoft Purview sensitivity labels.
• Create a Microsoft Dataverse table for the departments.
• From Copilot Studio, configure the SharePoint tool.
• Upgrade to SharePoint Premium.

---

Explanation/Reference:

Explanation:

Box 1: From Copilot Studio, add SharePoint as a knowledge source

Box 2: From Copilot Studio, configure the SharePoint tool.

Box 1: From Copilot Studio, add SharePoint as a knowledge source

Enable the agent to answer user questions about company policies.

To enable a Microsoft Copilot Studio agent to answer questions from a large SharePoint Online library using the Department column as a filter, you must configure Generative Answers with specific metadata filtering.

*-> 1. Configure SharePoint as a Knowledge Source Add the Source: In Copilot Studio, go to the Knowledge tab and select Add knowledge. Choose SharePoint and provide the URL of your site or specific document library.

Authentication: Ensure Manual Authentication with Microsoft Entra ID is configured. The agent requires the Sites.Read.All and Files.Read.All scopes to access documents on behalf of the user.

Indexing: Note that indexing tens of thousands of files can take significant time (days or weeks).

1. Enable Metadata Filtering (Department Column) To ensure the agent only searches policies relevant to a user's department, you must use Advanced Settings to filter the search results based on your custom column

Box 2: From Copilot Studio, configure the SharePoint tool.

Ensure that the agent can identify which departments and policies are connected.

The SharePoint tool can be configured directly from Microsoft Copilot Studio to act as a knowledge source, allowing your AI agent to read files, documents, and lists from SharePoint to provide answers.

Note:

To ensure your Copilot Studio agent effectively identifies and connects your "Department" metadata with specific policies across tens of thousands of documents, you must address both search indexing and agent instructions.

To ensure that your Microsoft Copilot Studio agent can identify and filter documents based on the Department column from your SharePoint library, you should configure the Advanced settings of your SharePoint knowledge source to use KQL (Keyword Query Language) filters.

Incorrect:

Upgrade to SharePoint Premium Configuring a Microsoft Copilot Studio agent to filter a SharePoint knowledge source using KQL (Keyword Query Language) for a Department column typically requires advanced filtering capabilities, but "SharePoint Premium" is not a strict prerequisite for the KQL configuration itself. Instead, the primary requirement is a Microsoft 365 Copilot or Copilot Studio license to access these advanced features.

QUESTION 6

You need to design a Microsoft Copilot Studio agent that meets the following requirements:

Supports interactive speech responses Optimizes decision-making and the accuracy of responses

What should you include in the design for each requirement? To answer, drag the appropriate options to the correct requirements. Each option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Options

• A deep reasoning model
• Azure Language in Foundry Tools
• Azure AI Speech
• Speech Synthesis Markup Language (SSML)

Answer Area

• Supports interactive speech responses:
• Optimizes decision-making and response accuracy:

---

Box 1: Copilot Studio voice features Supports interactive speech responses

Box 2: A deep reasoning model Optimizes decision-making and the accuracy of responses

Explanation/Reference:

Explanation:

Box 1: Copilot Studio voice features Supports interactive speech responses

To support interactive speech responses in a Microsoft Copilot Studio agent, you must incorporate specialized voice features and capabilities. These features enable the agent to move beyond chat-based interactions to handle voice-based input (speech-to-text) and output (text-to-speech).

Box 2: A deep reasoning model Optimizes decision-making and the accuracy of responses

Integrating a deep reasoning model (specifically Azure OpenAI o3) into Microsoft Copilot Studio optimizes decision-making and accuracy by enabling multi-step analysis, logical deduction, and the handling of complex, multi-turn conversations. This capability, enabled via the "reason" keyword in instructions, allows agents to analyze large datasets and provide context-aware, transparent answers, ideal for scenarios like financial analysis or compliance

QUESTION 7

You are designing a low-code AI business solution by using Microsoft Copilot Studio.

The solution must include an agent that automates tasks by simulating user interactions across third-party apps and websites, such as clicking buttons, entering text, and extracting information from screens.

You need to recommend what to include in the agent.

What should you recommend?

A. Model Context Protocol (MCP)

B. a natural language understanding + (NLU+) model in Copilot Studio

C. Computer Use in Copilot Studio

D. Copilot skills

---

Correct Answer: C

Explanation/Reference:

Explanation:

In Microsoft Copilot Studio, you can use the computer use tool (currently in preview) to build low-code agents that automate tasks by simulating human interactions on a Windows computer.

Key Capabilities of Computer Use UI Interaction: Agents can interact with any system featuring a graphical user interface (GUI), including third-party websites and desktop applications.

*-> Human-like Actions: The tool enables the agent to click buttons, select menus, enter text into fields, and scroll, mimicking a human user.

No API Required: It is particularly useful for automating legacy systems or applications that lack direct API connectors.

Vision-Based Reasoning: Powered by Computer-Using Agents (CUA), the tool uses AI to "see" the screen, allowing it to adapt in real time if button positions or layouts change.

*-> Low-Code Setup: You define what the agent should do using natural language instructions rather than complex coding.

Reference:

QUESTION 8

You need to recommend a solution to integrate a Microsoft Copilot agent with a Microsoft Dynamics 365 Contact Center chat channel.

The agent must respond to customer questions and hand off the conversation to a live customer service representative when the customer requests an escalation.

What should you recommend?

A. Build an agent flow.

B. Configure the Conversation Start topic.

C. Configure a skill.

D. Call a Microsoft Power Automate connector.

E. Configure the Escalate topic.

---

Correct Answer: E Section: (none)

Explanation/Reference:

Explanation:

To hand off a conversation from a Microsoft Copilot agent to a live representative in Dynamics 365 Contact Center, you must configure the Escalate system topic to include a Transfer conversation node. This ensures that when a customer requests an escalation, the agent seamlessly passes the full chat history and context to the live agent.

Steps to Configure the Escalate Topic Open the Escalate Topic: In Microsoft Copilot Studio, navigate to Topics, select the System tab, and open the Escalate topic.

Add a Transfer Node:

Delete any default "no one available" messages if they do not fit your workflow.

Select the Add node icon (+), go to Topic Management, and select Transfer conversation.

Include Context (Optional): You can add a Private message to agent within the node. This message is only visible to the live representative and helps them quickly understand the customer's needs.

Save and Publish: Save your changes and publish the agent to apply the new escalation logic.

QUESTION 9

A company has a customer order system that creates sales orders manually.

You need to design an AI solution to automate the following tasks as part of the system:

Save the order details to a database.

Update the order status in the database.

Extract the order details from an order file.

Prepare and send a confirmation email to customers.

The solution must minimize development effort and support intelligent automation and solution integration.

What should you include in the design?

A. a workflow in Azure Logic Apps

B. a multi-agent solution that uses the Semantic Kernel SDK

C. a multi-agent solution that uses Microsoft Foundry Agent Service

D. a Microsoft Copilot Studio agent that uses Microsoft Power Automate workflows

---

Correct Answer: D Section: (none)

Explanation/Reference:

Explanation:

To create this system, you'll need to integrate Microsoft Copilot Studio with Power Automate and AI Builder. This combination allows your agent to not only "talk" but also "act" by executing complex backend workflows.

Solution Architecture Front-end: A Copilot Studio agent serves as the interface, receiving order requests or files from customers.

Brain (Logic): Power Automate cloud flows act as the "skills" for your agent, handling all database and email operations.

Data Extraction: AI Builder (Document Processing) extracts specific fields (like Item ID, Quantity, or Customer Name) from uploaded order files.

Storage: Microsoft Dataverse or SQL Server functions as the database to save and update order records

QUESTION 10

You are designing an AI strategy for Microsoft Dynamics 365 finance and operations apps. You are evaluating the use of Microsoft Copilot Studio to provide in-app help and guidance based on generative AI general knowledge.

You need to recommend which knowledge sources to include in the generative help and guidance agent. The solution must minimize the risk of generating inaccurate responses.

What should you recommend? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

这是一道经典的微软认证考试（多为 PL-200、PL-100 或 Copilot Studio / Power Platform 相关科目）中的 Hot Area（热区选择题）。

以下为您精确提取的题目文本、背景知识解析以及常见考点答案。

---

Hot Area:

Answer Area

• Custom knowledge sources:
  • [ ] Must be uploaded to the agent (必须上传到智能体)
  • [ ] Must be excluded from the agent (必须从智能体中排除)
  • [ ] Are not supported (不支持)
• AI general knowledge:
  • [ ] Must be enabled for the agent (必须为智能体启用)
  • [ ] Must be disabled for the agent (必须为智能体禁用)
  • [ ] Is not supported (不支持)

---

Explanation/Reference:

Explanation:

Box 1: Must be uploaded to the agent Custom knowledge sources

Box 2: Must be enabled for the agent AI general knowledge

To implement a generative AI agent for in-app help in Dynamics 365 Finance and Operations while minimizing inaccuracies, you must configure the agent in Microsoft Copilot Studio by uploading specific knowledge sources and enabling general AI knowled

1. Upload Custom Knowledge Sources To ensure the agent provides accurate, organization-specific guidance, upload your internal documentation directly to the agent

2. Enable General AI Knowledge To allow the agent to use its own broad generative AI knowledge for general inquiries:

Open Microsoft Copilot Studio and select the Dataverse environment linked to your Finance and Operations apps.

Navigate to Agents and open the specific agent named Copilot for finance and operations apps.

On the Overview tab, find the Knowledge section and set Allow the AI to use its own general knowledge to Enabled.

Publish the changes to make this capability available in the D365 F&O sidecar.

QUESTION 11

You need to design a multi-agent solution that will include a custom agent. The solution must meet the following requirements:

Define the rules and constraints that the agent must follow.

Automate a backend process that involves data movement between services and runs independently of the agent's reasoning steps.

What should you include in the design for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

这是一道关于 Microsoft Copilot Studio / Power Platform 术语及功能应用的热区选择题。

以下为您提取的 Markdown 格式题目文本，以及标准的答案解析：

Answer Area

• Define rules and constraints:

  • [ ] Agent flows
  • [ ] Conversation topics
  • [ ] Microsoft Power Automate cloud flow

• Automate a backend process:

  • [ ] Conversation topics
  • [ ] Microsoft Power Automate cloud flow
  • [ ] Microsoft Power Pages

---

Box 1: Conversation topics

Box 2: Microsoft Power Automate cloud flow

Box 1: Conversation topics Define the rules and constraints that the agent must follow.

In a Microsoft AI project using Microsoft Copilot Studio, you define the rules, constraints, and dialogue paths for a custom agent primarily through Topics. Topics act as the agent's "competencies," determining how a conversation plays out based on specific user intents.

To use topics for defining agent behavior and constraints, follow these core principles:

Define Conversation Paths: Use topics to map out discrete, structured paths for the agent to follow. This allows you to enforce specific procedures, such as user verification, before providing sensitive information.

Set Triggers: Each topic begins with a trigger (phrases, keywords, or events) that signals when the agent should switch to a specific set of rules or logic.

Enforce Logic via Nodes: Within a topic, use nodes—such as questions, conditions, and actions—to define the logic, variables, and branching paths the agent must follow.

Modularize with "Bite-size" Topics: Break down complex agent logic into smaller, manageable topics. You can use the Redirect node to pass the conversation (and its constraints) from one topic to another.

Handle Errors and Fallbacks: Use System Topics (like On Error or Escalate) to define how the agent should behave when it hits a constraint it cannot resolve or fails to understand a query.

Box 2: Microsoft Power Automate cloud flow Automate a backend process that involves data movement between services and runs independently of the agent's reasoning steps.

In a Microsoft multi-agent project, you can use Power Automate cloud flows to handle backend data movement independently of an agent's reasoning steps. This approach is often referred to as classic orchestration.

By offloading structured, rule-based tasks to a cloud flow, you ensure that high-volume data operations or multi-service integrations remain deterministic and reliable, while your custom agents focus on dynamic, probabilistic decision-making.

QUESTION 12

A company uses Microsoft 365 and Dynamics 365.

You need to recommend a solution to automatically summarize email threads, generate suggested replies in Microsoft Outlook, and provide meeting preparation summaries that include relevant customer relationship management (CRM) data.

Solution: You recommend Microsoft 365 Copilot for Sales.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: A

Explanation/Reference:

Explanation:

Correct:

• You recommend Microsoft 365 Copilot for Sales.

Incorrect:

• You recommend a classic Microsoft Dataverse workflow.
• You recommend a Microsoft 365 Copilot agent template.

Note:

In the described scenario, Microsoft 365 Copilot for Sales acts as the primary bridge between your productivity tools and CRM data. It integrates directly into Microsoft Outlook and Teams to surface realtime insights from Dynamics 365 Sales or Salesforce.

Key capabilities for this specific workflow include:

Automated Email Summarization: Copilot scans long email threads in Outlook to extract key points, highlights, and BANT (Budget, Authority, Need, Timeline) data. If the sender is an external contact recognized in your CRM, the summary is automatically enriched with relevant account and opportunity data.

Suggested Email Replies: When replying to customer emails, Copilot generates drafts based on the context of the conversation and existing CRM data. You can use predefined response categories (e.g., "Reply to an inquiry," "Offer a proposal") or custom prompts to include specific opportunity details in the draft.

Meeting Preparation Summaries: Before a scheduled meeting, Copilot for Sales provides a "preparation card" in Teams or Outlook. This summary includes:

• CRM Data: Matched opportunity and account attributes.

• Contextual History: Summaries of past email exchanges and the last three seller notes.

• Strategic Insights: Key risks, follow-up actions, and discussion points from previous interactions.

QUESTION 13

A company uses Microsoft 365 and Dynamics 365.

You need to recommend a solution to automatically summarize email threads, generate suggested replies in Microsoft Outlook, and provide meeting preparation summaries that include relevant customer relationship management (CRM) data.

Solution: You recommend a classic Microsoft Dataverse workflow.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: B

Explanation/Reference:

Explanation:

Correct:

• You recommend Microsoft 365 Copilot for Sales.

Incorrect:

• You recommend a classic Microsoft Dataverse workflow. * You recommend a Microsoft 365 Copilot agent template.

Note:

In the described scenario, Microsoft 365 Copilot for Sales acts as the primary bridge between your productivity tools and CRM data. It integrates directly into Microsoft Outlook and Teams to surface realtime insights from Dynamics 365 Sales or Salesforce.

Key capabilities for this specific workflow include:

Automated Email Summarization: Copilot scans long email threads in Outlook to extract key points, highlights, and BANT (Budget, Authority, Need, Timeline) data. If the sender is an external contact recognized in your CRM, the summary is automatically enriched with relevant account and opportunity data.

Suggested Email Replies: When replying to customer emails, Copilot generates drafts based on the context of the conversation and existing CRM data. You can use predefined response categories (e.g., "Reply to an inquiry," "Offer a proposal") or custom prompts to include specific opportunity details in the draft.

Meeting Preparation Summaries: Before a scheduled meeting, Copilot for Sales provides a "preparation card" in Teams or Outlook. This summary includes:

• CRM Data: Matched opportunity and account attributes.

• Contextual History: Summaries of past email exchanges and the last three seller notes.

• Strategic Insights: Key risks, follow-up actions, and discussion points from previous interactions.

QUESTION 14

A company uses Microsoft 365 and Dynamics 365.

You need to recommend a solution to automatically summarize email threads, generate suggested replies

in Microsoft Outlook, and provide meeting preparation summaries that include relevant customer relationship management (CRM) data.

Solution: You recommend a Microsoft 365 Copilot agent template.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: B

Explanation:

Correct:

• You recommend Microsoft 365 Copilot for Sales.

Incorrect:

• You recommend a classic Microsoft Dataverse workflow. * You recommend a Microsoft 365 Copilot agent template.

Note:

In the described scenario, Microsoft 365 Copilot for Sales acts as the primary bridge between your productivity tools and CRM data. It integrates directly into Microsoft Outlook and Teams to surface realtime insights from Dynamics 365 Sales or Salesforce.

Key capabilities for this specific workflow include:

Automated Email Summarization: Copilot scans long email threads in Outlook to extract key points, highlights, and BANT (Budget, Authority, Need, Timeline) data. If the sender is an external contact recognized in your CRM, the summary is automatically enriched with relevant account and opportunity data.

Suggested Email Replies: When replying to customer emails, Copilot generates drafts based on the context of the conversation and existing CRM data. You can use predefined response categories (e.g., "Reply to an inquiry," "Offer a proposal") or custom prompts to include specific opportunity details in the draft.

Meeting Preparation Summaries: Before a scheduled meeting, Copilot for Sales provides a "preparation card" in Teams or Outlook. This summary includes:

• CRM Data: Matched opportunity and account attributes.

• Contextual History: Summaries of past email exchanges and the last three seller notes.

• Strategic Insights: Key risks, follow-up actions, and discussion points from previous interactions.

QUESTION 15

You need to design an application lifecycle management (ALM) process for a Microsoft Power Platform environment that contains a solution named Solution1.

Solution1 must include a custom connector for Copilot in Microsoft Dynamics 365 Customer Service. Solution1 must meet the following requirements:

Ensure that the custom connector can be deployed consistently across environments as part of the ALM process.

Allow the custom connector to be edited only in the development environment.

What should you include in the design?

A. Add the custom connector to GitHub.

B. Share the custom connector.

C. Create the custom connector in the default solution.

D. Add the custom connector to Solution1.

---

Correct Answer: D Section: (none)

Explanation/Reference:

Explanation:

To implement a consistent and secure Application Lifecycle Management (ALM) process for your custom connector, you should add the custom connector to the solution.

Adding the custom connector as a component of a solution is the standard method for ensuring it can be packaged and deployed across environments.

QUESTION 16

A company uses a Microsoft Copilot Studio agent to automate tasks in a web app.

During testing, you discover that the automation sometimes fails because of frequent changes to the app's user interface.

You need to recommend a solution to ensure that the agent successfully automates the tasks. The solution must minimize changes to the agent.

What should you include in the recommendation?

A. Computer Use in Copilot Studio

B. custom models in Azure AI Studio

C. conversation topics in Copilot Studio

D. an agent flow in Copilot Studio

---

Correct Answer: A

Explanation/Reference:

Explanation:

The Computer Use tool in Microsoft Copilot Studio is specifically designed to remedy automation failures caused by UI changes with minimal manual intervention.

Unlike traditional Robotic Process Automation (RPA), which relies on rigid selectors or fixed coordinates that break when a layout shifts, Computer Use is powered by Computer-Using Agents (CUA). This AI model combines computer vision with advanced reasoning to "see" the screen like a human, allowing it to adapt to interface changes in real-time.

Why Computer Use Fixes UI Fragility Visual Reasoning: Instead of looking for a specific HTML tag that might change, the agent looks for the visual concept of a button (e.g., "Submit" or a "plus icon").

Real-Time Adaptation: If a button moves from the left side of the screen to the right, the agent simply scans the screen and finds its new location without requiring you to update any code or scripts.

Natural Language Instructions: You describe the task in plain English (e.g., "Log into the portal and download the latest invoice"). If the portal changes its navigation menu, the AI reasons through the new layout to find the invoice link.

Self-Healing Properties: Because the agent makes decisions at each step based on the current visual state, it effectively "self-heals" during execution, overcoming obstacles that would typically crash a legacy bot.

QUESTION 17

A company processes invoices stored across multiple systems in multiple formats. You need to implement an AI solution to automate the invoice processing. The solution must meet the following requirements:

Automate multi-step invoice processing tasks, including document analysis, data validation, and approval routing.

Enable users to interact directly via Microsoft Teams to review and approve invoices.

Minimize development efforts to define and customize approval workflows.

What should you include in the solution?

A. Azure Document Intelligence in Foundry Tools and Azure Logic Apps

B. a SharePoint agent

C. Microsoft Copilot Studio and AI Builder

D. Azure OpenAI and Azure Functions

---

Correct Answer: C

Explanation/Reference:

Explanation:

To automate invoice processing using Microsoft Copilot Studio and AI Builder, you can build an "Intelligent Invoicing Agent" that serves as the central orchestration layer. This solution combines AI-driven data extraction with low-code approval workflows accessible directly within Microsoft Teams.

Solution Architecture The most efficient approach uses Copilot Studio as the "brain" and AI Builder as the "eyes" to read documents.

Extraction Layer (AI Builder): Uses the Prebuilt Invoice Model to automatically identify and extract data like vendor name, date, and total amount without manual training.

Orchestration Layer (Copilot Studio): Hosts "Agent Flows" (advanced workflows) that manage the end-to-end logic, from receiving a file to routing it for approval.

Interaction Layer (Microsoft Teams): Users upload invoices or receive approval cards directly in a chat window, eliminating the need to switch between different accounting apps.

QUESTION 18

You need to design a Microsoft Copilot Studio agent for customer support.

The agent must securely retrieve product warranty data from a REST API. The solution must minimize development effort.

What should you include in the design?

A. Export the agent as a managed solution and customize the agent in Power Apps.

B. Create a custom connector in Copilot Studio and use the connector to call the API.

C. Use a Microsoft Power Automate desktop flow to screen scrape the warranty data.

D. Add the warranty data to the Fallback topic.

---

Correct Answer: B

Explanation/Reference:

Explanation:

To securely retrieve data from a REST API for a customer support agent in Microsoft Copilot Studio while minimizing development, creating a custom connector is a highly efficient approach. This method acts as a no-code/low-code wrapper around your API, allowing the agent to perform actions or fetch real-time information.

Implementation Steps

1. Create the Custom Connector

You can build this within Power Apps or Power Automate under the Data or Custom Connectors menu.

1. Add the Connector as an Action

Once the connector is created and published, you can add it directly to your agent.

QUESTION 19

A company has an ecommerce support portal that uses Microsoft Dataverse.

You are designing a Microsoft Copilot Studio agent for the portal. The agent must meet the following requirements:

• Respond with a default help message when the user input is unclear.

• Initiate external processes, such as retrieving the order status, when users make specific requests. Generative orchestration will be enabled for the solution.

You need to recommend a feature for each requirement.

What should you recommend? To answer, drag the appropriate features to the correct requirements. Each feature may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Answer Area

• Define rules and constraints:

  • [ ] Agent flows
  • [ ] Conversation topics
  • [ ] Microsoft Power Automate cloud flow

• Automate a backend process:

  • [ ] Conversation topics
  • [ ] Microsoft Power Automate cloud flow
  • [ ] Microsoft Power Pages

---

Box 1: The Fallback topic

Box 2: A tool (connector)

Box 1: The Fallback topic

Respond with a default help message when the user input is unclear.

To ensure your Microsoft Copilot Studio agent responds with a default help message when user input is unclear, you must configure the System Fallback topic. This topic is specifically designed to trigger when the agent cannot match the user's intent to any existing topics or knowledge sources.

Box 2: A tool (connector)

Initiate external processes, such as retrieving the order status, when users make specific requests.

In Microsoft Copilot Studio, when generative orchestration is enabled, you use Actions (specifically those powered by Power Platform Connectors) to initiate external processes like retrieving an order status. When a user asks a specific request (e.g., "What is the status of my order?"), the generative orchestrator identifies that it cannot fulfill the request with its existing knowledge and looks for an available Action or Tool to bridge the gap.

Key Tool: Power Platform Connectors To retrieve data from an external system, you would typically use one of the following:

Prebuilt Connectors: Microsoft offers over 1,400 ready-to-use connectors for popular systems like SAP, Oracle, or SQL Server.

Custom Connectors: If your order data is in a proprietary or niche API, you can create a custom connector to define exactly how the agent should talk to that external service.

Power Automate Flows: You can wrap complex logic (like multi-step lookups or data formatting) into a flow and add it as an action. The agent can then "call" this flow, pass it an Order ID, and receive the status back.

QUESTION 20

A company uses Microsoft Dynamics 365 to manage service operations. Dispatchers coordinate service requests, and technicians perform scheduled on-site work.

You need to design a solution that will use Microsoft Copilot to improve the efficiency of the service operations. The solution must meet the following requirements:

Provide AI-driven assistance to help staff organize and resolve work orders.

Deliver contextual AI support to frontline workers as they prepare for and complete customer appointments.

Which two components should you include in the design? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Copilot Service workspace

B. Copilot in Outlook

C. Dynamics 365 Customer Service

D. Copilot in Customer Service

E. Copilot in Field Service

F. the Dynamics 365 Field Service mobile app

---

Correct Answer: BE

Explanation/Reference:

To enhance Microsoft Dynamics 365 Field Service with Microsoft Copilot for dispatchers and technicians, the following additional components and configurations are needed:

Essential Copilot Enabling Components [E] Dynamics 365 Field Service License: Copilot for Field Service is included within the standard app, but must be enabled by an administrator in the Power Platform admin center.

[B] Copilot in Outlook & Teams: To enable dispatchers to turn emails into work orders and manage schedules directly in their flow of work, the Dynamics 365 Field Service for Outlook and Field Service app in Teams (preview) need to be configured.

New Field Service Mobile Experience: Technicians must have the latest mobile app (available in preview) enabled, which allows for natural language inputs, voice-to-text notes, and photo attachments.

QUESTION 21

A company uses Microsoft Foundry agents.

You need to ensure that an agent can dynamically use external tools at runtime without updating the agent.

What should you include in the solution?

A. a Microsoft Foundry hub

B. a Model Context Protocol (MCP) server

C. Azure AI Search

D. Microsoft Copilot Studio

---

Correct Answer: B

Explanation/Reference:

n Microsoft Foundry, the Model Context Protocol (MCP) is the architectural standard used to decouple an agent's logic from its toolset, allowing it to discover and use external tools at runtime without requiring code updates or re-deployment.

Why an MCP Server is Required Traditionally, integrating a tool required "hardcoding" its schema into the agent's definition. MCP replaces this with a dynamic discovery model:

Decoupling: The agent is only configured with the MCP server endpoint rather than individual tool definitions.

Runtime Discovery: When the agent starts a session, it queries the MCP server for a manifest of available tools, their parameters, and descriptions.

Zero-Update Scaling: You can add new capabilities to the MCP server (e.g., a new database query or API connection), and the agent will automatically "see" and use them in the next turn without any changes to the agent itself.

QUESTION 22

A company has a Microsoft Dynamics 365 Sales environment that has Microsoft Copilot enabled.

You need to customize Copilot by tailoring how opportunity summaries are generated or how they are presented to users.

Solution: You add fields to the opportunity summary.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: A

Explanation/Reference:

Correct:

• You add fields to the opportunity summary.

Incorrect:

• You build Microsoft Power Automate flows to trigger customized Copilot summaries.
• You configure AI Builder lead scoring models to influence opportunity summaries.

Note:

To customize Microsoft Copilot opportunity summaries and incorporate AI Builder lead scoring data, you must configure the specific fields Copilot uses to ground its generative AI outputs.

By default, Copilot for Sales generates summaries using a set of predefined fields. To "influence" these summaries with scoring data, you need to add the predictive score and grade fields to the Opportunity summary configuration.

Step-by-Step Configuration Switch Area: In the Sales Hub app, select the Change area menu in the bottom-left corner and choose App Settings.

Navigate to Copilot: Under General Settings, select Copilot.

Select Entity: Choose the Opportunities tab.

Add Fields:

• Click Add fields.
• Select the checkboxes for the fields you want to include.
• You can select out-of-the-box, custom, and related table fields.
• Save: Click Add and then Save your changes to update the summary configuration.

QUESTION 23

A company has a Microsoft Dynamics 365 Sales environment that has Microsoft Copilot enabled.

You need to customize Copilot by tailoring how opportunity summaries are generated or how they are presented to users.

Solution: You build Microsoft Power Automate flows to trigger customized Copilot summaries.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: B

Explanation/Reference:

Explanation:

Correct:

• You add fields to the opportunity summary.

Incorrect:

• You build Microsoft Power Automate flows to trigger customized Copilot summaries.
• You configure AI Builder lead scoring models to influence opportunity summaries.

Note:

To customize Microsoft Copilot opportunity summaries and incorporate AI Builder lead scoring data, you must configure the specific fields Copilot uses to ground its generative AI outputs.

By default, Copilot for Sales generates summaries using a set of predefined fields. To "influence" these summaries with scoring data, you need to add the predictive score and grade fields to the Opportunity summary configuration.

Step-by-Step Configuration Switch Area: In the Sales Hub app, select the Change area menu in the bottom-left corner and choose App Settings.

Navigate to Copilot: Under General Settings, select Copilot.

Select Entity: Choose the Opportunities tab.

Add Fields:

• Click Add fields.

• Select the checkboxes for the fields you want to include.

• You can select out-of-the-box, custom, and related table fields.

• Save: Click Add and then Save your changes to update the summary configuration.

QUESTION 24

A company has a Microsoft Dynamics 365 Sales environment that has Microsoft Copilot enabled.

You need to customize Copilot by tailoring how opportunity summaries are generated or how they are presented to users.

Solution: You configure AI Builder lead scoring models to influence opportunity summaries.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: B

Explanation/Reference:

Correct:

• You add fields to the opportunity summary.

Incorrect:

• You build Microsoft Power Automate flows to trigger customized Copilot summaries.
• You configure AI Builder lead scoring models to influence opportunity summaries

Note: To customize Microsoft Copilot opportunity summaries and incorporate AI Builder lead scoring data, you must configure the specific fields Copilot uses to ground its generative AI outputs.

By default, Copilot for Sales generates summaries using a set of predefined fields. To "influence" these summaries with scoring data, you need to add the predictive score and grade fields to the Opportunity summary configuration.

Step-by-Step Configuration Switch Area: In the Sales Hub app, select the Change area menu in the bottom-left corner and choose App Settings.

Navigate to Copilot: Under General Settings, select Copilot.

Select Entity: Choose the Opportunities tab.

Add Fields:

• Click Add fields.

• Select the checkboxes for the fields you want to include.

• You can select out-of-the-box, custom, and related table fields.

• Save: Click Add and then Save your changes to update the summary configuration.

QUESTION 25

A company has a Microsoft Dynamics 365 Sales environment that has Microsoft Copilot enabled.

You need to customize Copilot by tailoring how opportunity summaries are generated or how they are presented to users.

Solution: You add the opportunity summary widget to the Opportunity form.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: B

Explanation/Reference:

Explanation:

Correct:

• You add fields to the opportunity summary.

Incorrect:

• You add the opportunity summary widget to the Opportunity form.

• You build Microsoft Power Automate flows to trigger customized Copilot summaries.

• You configure AI Builder lead scoring models to influence opportunity summaries

Note:

To customize Microsoft Copilot opportunity summaries and incorporate AI Builder lead scoring data, you must configure the specific fields Copilot uses to ground its generative AI outputs.

By default, Copilot for Sales generates summaries using a set of predefined fields. To "influence" these summaries with scoring data, you need to add the predictive score and grade fields to the Opportunity summary configuration.

Step-by-Step Configuration Switch Area: In the Sales Hub app, select the Change area menu in the bottom-left corner and choose App Settings.

Navigate to Copilot: Under General Settings, select Copilot.

Select Entity: Choose the Opportunities tab.

Add Fields:

Click Add fields.

Select the checkboxes for the fields you want to include.

You can select out-of-the-box, custom, and related table fields.

Save: Click Add and then Save your changes to update the summary configuration.

Deploy AI-powered business solutions

Testlet 1

Overview

Contoso, Ltd. is a high-tech manufacturing company that uses Microsoft Dynamics 365 Finance. Dynamics 365 Supply Chain Management, and Dynamics 365 Commerce for its North American operations. The company designs and develops innovative products that have many patents and proprietary technologies. The patents and engineering designs are closely guarded secrets.

Contoso executives want to integrate and adopt AI solutions to help scale the company in preparation for an anticipated period of rapid growth.

The company has multiple legal entities and Azure subscriptions that will be used in the adopted AI solutions.

Requirements

• AI Adoption The following executives will have specific responsibilities in the overall AI adoption:

• Chief Technology Officer (CTO): Select one Dynamics 365 Finance, Dynamics 365 Supply Chain Management or Dynamics 365 Commerce prebuilt AI agent and one custom Microsoft Copilot Studio AI agent to prioritize and deploy during the initial AI adoption phase.

• Chief Information Officer (CIO): Ensure that appropriate security labels are assigned to the data used by the AI agents.

• Chief Financial Officer (CFO): Analyze the return on investment (ROI) for the AI agents being deployed. Chief Information Security Officer (CISO): Discover and inventory AI resources for auditing.

• Chief Executive Officer (CEO): Ensure that all solutions adhere to industry-standard responsible AI practices

All AI initiatives and agents will have a detailed business use case, a defined audience profile, and an estimated ROI that will compare the cost savings of the current process against the estimated costs of using the new AI solutions.

The company's research and development (R&D) department already has a custom Model Context Protocol (MCP) server that contains comprehensive product specifications and compliance data

Prebuilt AI Agent

The CTO has NOT yet selected which prebuilt AI agent to use in Dynamics 365 Supply Chain Management. The CTO wants to view available agent templates to identify which agent will add the most business value.

Depending on which high-priority AI agents are identified, its agent capabilities must be previewed in a discovery meeting with the relevant business operation stakeholders.

Custom AI Agent

Contoso has identified the following custom AI agent requirements:

• The custom AI agent will use data from Dynamics 365 Supply Chain Management to answer questions for the manufacturing team as a low-code solution.

• The custom AI agent will be accessible from within Microsoft Teams.

• The custom AI agent must be designed to eventually connect to other agents that can be selected based on their description.

• The topics used in the custom AI agent will be selected based NOT on a trigger phrase, but on a description of the purpose of the query, to make the interactions more conversational.

• The custom AI agent must be able to answer questions about product specifications by using existing technologies. The product specifications are maintained by the R&D department.

• The custom AI agent must be integrated with and accessible from Dynamics 365 Supply Chain Management.

• The custom AI agent must be able to use Dynamics 365 Supply Chain Management business logic that is stored outside of the application.

Analysis, Reporting, and Troubleshooting

Contoso has identified the following analysis, reporting, and troubleshooting requirements:

• The CFO will analyze all the AI solutions quarterly to compare the estimated ROI against actual measured efficiencies and adoption. The CFO will use the Copilot Studio agent usage estimator to perform this analysis.

• The CISO wants to identify how much sensitive data was accessed for a given AI agent run and who accessed the data. Too much sensitive data accessed by a single user might indicate a high security risk.

• The CTO wants to track user feedback on the quality of the AI agent responses during user interactions with the agents. Consistently poor feedback will trigger an escalated reengineering discussion.

• The CEO wants a quarterly assessment of all the required metrics for their specific responsibilities. The tools used for the assessments must be Microsoft-recommended and must verify reliability, interpretability, fairness, and compliance.

• The CFO wants to identify how many interactions with the AI agents are abandoned on a given day as compared to resolved conversations. Too many abandoned sessions might indicate that Copilot Studio credits are being used inefficiently by end users.

QUESTION 1

Which two components for the custom AI agent should you include in the application lifecycle management (AIM) process? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. an Azure package

B. a ZIP package

C. a Microsoft Power Platform solution

D. a Cloud Scale Unit (CSU) package

E. an X++model

---

Correct Answer: BC Section: (none)

Explanation/Reference:

• [C] A Microsoft Power Platform solution is the standard container for transporting and managing customizations across the Power Suite (Copilot Studio, Power Automate, and Power Apps). It perfectly aligns with the specific requirements.

• [B] Based on the application lifecycle management (ALM) process for a Microsoft Power Platform solution that integrates with Dynamics 365 Supply Chain Management, you should use a ZIP package.

Recommended ALM Component In the Microsoft Power Platform ecosystem, the standard unit of deployment for ALM is a Solution, which is exported and transported as a ZIP package.

ZIP package: This is the standard format for Power Platform solutions containing Copilot Studio agents, Power Automate flows, and custom connectors used to bridge Dynamics 365 and Teams.

Incorrect:

[Not A] Azure package: Typically refers to Azure-native resources; while used for custom coding, the Power Platform solution itself is handled via ZIP exports.

[Not D] Cloud Scale Unit (CSU) package: Specifically for commerce or edge workloads, not for deploying general AI agents.

[Not E] X++ model is used for core code changes inside Dynamics 365 Finance & Operations, but not for the lowcode Power Platform/Copilot Studio orchestration described.

QUESTION 2

Which tools should you recommend to assist the CISO and the CIO with their specific responsibilities? To answer, drag the appropriate tools to the correct executives. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Tools (待拖拽选项)
Azure Blob Storage
Azure Resource Graph Explorer
Copilot Studio
Microsoft Purview

Answer Area (答题区)

• CISO (首席信息安全官):
  • [ 拖拽目标位置 1 ]
• CIO (首席信息官):
  • [ 拖拽目标位置 2 ]

---

Box 1: Microsoft Purview

Box 2: Microsoft Purview

Box 1: Microsoft Purview CISO

Scenario:

The CISO will audit all the AI solutions monthly for compliance and security.

The CISO wants to identify how much sensitive data was accessed for a given AI agent run and who accessed the data. Too much sensitive data accessed by a single user might indicate a high security risk.

-Microsoft Purview is the primary tool for this scenario. It provides a unified governance and security platform that integrates directly with Microsoft Agent 365 and Dynamics 365 AI agents to audit interactions, track sensitive data access, and identify high-risk user behaviors.

Auditing Sensitive Data in AI Agent Runs Purview uses a combination of automated classification and audit logging to provide a granular view of every AI interaction.

Unified Audit Log: Automatically captures user and agent activities, including who initiated the interaction and when it occurred.

Resource Tracking: Audit records reference specific files, SharePoint sites, or Dataverse tables accessed by the agent during a run.

Data Classification: Identifies Sensitive Information Types (SITs)—such as credit card numbers, PII, or internal trade secrets—within both the user prompt and the agent's response.

Sensitivity Labels: Captures if accessed files have existing sensitivity labels, ensuring protection is maintained even when data is summarized by an agent.

Box 2: Microsoft Purview CIO

Scenario:

Chief Information Officer (CIO): Ensure that appropriate security labels are assigned to the data used by the AI agents.

Microsoft Purview is the primary tool for managing and assigning security labels to data used by AI agents in Microsoft Dynamics 365.

Within the Microsoft ecosystem, these "security labels" are formally known as Sensitivity Labels, and they are configured and published via the Microsoft Purview Information Protection service.

QUESTION 3

What should you recommend to assist the CEO with their specific responsibilities?

A. the Microsoft Service Trust Portal

B. Microsoft Foundry Tools

C. Microsoft Purview

D. the Responsible AI dashboard

E. Compliance Center

---

Correct Answer: D

Explanation/Reference:

Explanation:

Scenario: The CEO wants a quarterly assessment of all the required metrics for their specific responsibilities. The tools used for the assessments must be Microsoft-recommended and must verify reliability, interpretability, fairness, and compliance.

To ensure your Microsoft Dynamics 365 AI agent meets quarterly compliance and ethical standards, the Responsible AI (RAI) Dashboard in Azure Machine Learning is the primary recommended tool.

Microsoft recommends aligning quarterly assessments with their Responsible AI Standard v2, which focuses on six core principles: fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability.

QUESTION 4

Which Copilot Studio analytics metrics should you recommend to assist the executives with their specific responsibilities? To answer, drag the appropriate metrics to the correct executives. Each metric may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Select and Place:

Metrics (Options): * [ Effectiveness ] * [ Tool use ] * [ Satisfaction ] * [ Use ]

Answer Area:

• CFO concerns about Copilot Studio credit usage: [ ________ ]
• CTO concerns about poor feedback on AI agent responses: [ ________ ]

---

Box 1: Effectiveness

Box 2: Satisfaction

Box 1: Effectiveness

CFO concerns about Copilot Studio credit usage

Scenario: The CFO wants to identify how many interactions with the AI agents are abandoned on a given day as compared to resolved conversations. Too many abandoned sessions might indicate that Copilot Studio credits are being used inefficiently by end users.

To identify how many interactions with AI agents are abandoned compared to resolved, you should use the Effectiveness metrics.

In Microsoft Copilot Studio, Effectiveness specifically tracks Session Outcomes, which categorize every engaged conversation into one of three primary states:

Resolved: The user's issue was addressed, and the session ended successfully.

Abandoned: The user stopped interacting without reaching a resolution or escalation, or the session timed out.

Escalated: The conversation was handed over to a human agent.

Box 2: Satisfaction

CTO concerns about poor feedback on AI agent responses

Scenario: The CTO wants to track user feedback on the quality of the AI agent responses during user interactions with the agents. Consistently poor feedback will trigger an escalated reengineering discussion.

AI Overview To track user feedback on the quality of AI agent responses in Microsoft Copilot Studio (and Dynamics 365), you should use the Satisfaction analytics metric. Specifically, the Reactions chart within the Satisfaction section tracks user-provided feedback, which measures user perception of response quality.

Satisfaction (Reactions): This section captures direct user feedback (thumbs up/down) on individual answers and provides a ratio of positive to negative feedback, including specific user comments for detailed analysis.

Deploy AI-powered business solutions Testlet 2

Background

Fabrikam, Inc., is a global consumer goods company that is undergoing a digital transformation initiative to migrate its entire infrastructure to the Microsoft cloud. As a key element of this cloud migration, the company will implement Microsoft Dynamics 365 Sales, moving away from the current on-premises proprietary technologies used by its business-to-business (B2B) sales team.

As part of the cloud migration, Fabrikam will adopt an AI-first approach to its business solutions and implement AI solutions, wherever possible, to streamline operations.

Problem Statements

Fabrikam's infrastructure currently relies on various on-premises systems that require sales executives to use corporate computers with physical keyboards to access business information during customer interactions. Mobile phones cannot be used for these purposes, as the systems depend on keyboard input. As a result, the sales executives spend a lot of time using keyboards to search for data on several disparate systems and file servers, rather than focusing on the customers. This affects the customer experience.

Fabrikam stakeholders are concerned that users will be hesitant to adopt AI. If the AI initiatives are NOT adopted, cost savings will never be realized. Additionally, funding for future AI initiatives will depend on demonstrating an increase in AI adoption month over month. As the AI agent initiative for the sales team will be the first for Fabrikam, the rapid adoption of the agent is a high priority.

Planned Initiatives General

Fabrikam management has prioritized AI-driven projects to improve efficiency, customer engagement, and responsible AI adoption. The current application infrastructure is on-premises and must be migrated to the cloud to support the adoption of these technologies.

Infrastructure Migration

Fabrikam plans to migrate from its current on-premises infrastructure to a completely cloud-based topology; this will include user authentication, the security framework, and, primarily, the adoption of the services by end users.

All the data from the different systems will be consolidated into a single data source - a common data model that will use a Microsoft Dataverse environment as a single source of truth (SSOT) for the sales team.

Sales Cycle Enablement

To achieve the company's objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle:

Use low-code development to create a single AI agent that has Dataverse as its core component. Ensure that sales managers can access unanswered correspondence from prospects and intervene as appropriate.

Replace the previous proprietary software with Dynamics 365 Sales to track sales cycles and customer interactions.

Have the sales executives use Dynamics 365 Sales to track interactions for open opportunities and send follow-up communications to prospects.

Have the sales executives use handsfree headsets to interact with an AI agent when they have questions about internal policies or customer data.

Requirements

Infrastructure Migration

Fabrikam has identified the following infrastructure migration requirements:

• Azure must be used for all future infrastructure workloads.
• The company must follow Microsoft-recommended methodologies for infrastructure migration to the cloud.
• Any created AI agents must have their return on investment (ROI) calculated to ensure that the solution will save the company money.

Sales Cycle Enablement

Fabrikam has identified the following requirements for sales cycle enablement:

• The final AI agent must follow Microsoft recommendations for a conversational user experience.

• A designated checklist must be reviewed to ensure that the AI agent follows Microsoft deployment recommendations for a compliant solution.

• Detailed telemetry must be logged for the first created AI agent to help troubleshoot and optimize the agent during the initial AI agent adoption process.

• Unexpected AI agent actions must end in an escalation to a live representative. For example, a sales executive must be rerouted to a representative if the agent cannot answer a question after two failed attempts.

• The return on investment (ROI) of switching from the current process to the future process is required for stakeholder sign off.

• The sales team must use Dynamics 365 Sales to correspond with prospects more quickly and efficiently than currently.

• Sales managers must report on the adoption of the AI agent to key Fabrikam stakeholders on a monthly basis.

• Any sensitive information, such as user IDs and names, shared via the AI agent must be tracked for future auditing.

A. the Analytics tab in Microsoft Copilot Studio

B. Model Context Protocol (MCP)

C. Application Insights

D. Microsoft Foundry Tracing UI

E. Monitoring in Microsoft Foundry

---

Correct Answer: D

Explanation/Reference:

Fabrikam has identified the following requirements for sales cycle enablement:

Any sensitive information, such as user IDs and names, shared via the AI agent must be tracked for future auditing.

In a Microsoft AI solution involving an agent where you must track sensitive information for auditing, you should use the Microsoft Foundry Tracing UI.

Tracking and Auditing with Microsoft Foundry Tracing The Microsoft Foundry Tracing UI (part of Microsoft Foundry) provides end-to-end visibility into agent runs by capturing detailed telemetry through OpenTelemetry.

What is Captured: It automatically logs user inputs, model outputs, and tool arguments, which often contain sensitive information like names or IDs.

Auditing and Debugging: You can search, filter, and sort traces from the last 90 days to observe exactly how your agent responded during specific sessions.

Infrastructure: Traces are stored in Azure Application Insights, allowing you to apply standard enterprise access controls and retention policies.

QUESTION 2

Which existing tool and data should you use to gather the required metrics for stakeholder signoff for the AI agents? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

• Tool:

  • [ ] Microsoft Foundry
  • [ ] Azure Resource Monitor (ARM)
  • [ ] Dynamics 365 Sales
  • [ ] Microsoft Copilot Studio

• Data required for the tool:

  • [ ] the cumulative time spent on the task over the past year
  • [ ] the current cost to complete the tasks per instance
  • [ ] the current time to complete the task today per instance
  • [ ] the current cost of the Dynamics 365 Sales licenses

---

• Box 1: Microsoft Foundry

• Box 2: the current time to complete the task today per instance

Explanation/Reference:

Explanation:

Scenario:

The return on investment (ROI) of switching from the current process to the future process is required for stakeholder sign off.

Box 1: Microsoft Foundry Tool

To secure stakeholder sign-off for a Microsoft AI solution using AI agents and Dataverse, Azure AI Foundry (formerly Azure AI Studio) provides a structured framework to gather metrics across five key "ROI levers":

1. Identify Key ROI Metrics via Foundry Use the Foundry ROI Framework to categorize and collect data that compares the current manual process to the future AI-driven state.

2. Gather Data using Foundry Tools Foundry offers specific technical features to generate the evidence needed for your business case.

3. Calculate the ROI Once metrics are gathered, apply the standard Microsoft-recommended formula for the business case.

Box 2: the current time to complete the task today per instance Data required for the tool

In the Microsoft Foundry ROI framework, the metric for current time required to complete a task today is typically referred to as the Current Time per Instance or Task Duration (Baseline). This value serves as the primary "Before" benchmark to calculate the efficiency gains of the new AI agent solution.

QUESTION 3

Which tool should you recommend to help secure funding for future AI agent development?

A. Evaluations in Microsoft Foundry

B. the Azure Cost Optimization workbook

C. Azure Operator Insights

D. the Analytics tab in Microsoft Copilot Studio

E. Direct Preference Optimization (DPO)

---

Correct Answer: D

Explanation/Reference:

Explanation:

Scenario Requirements Any created AI agents must have their return on investment (ROI) calculated to ensure that the solution will save the company money.

-In a Microsoft AI migration, calculating the Return on Investment (ROI) for AI agents is essential for justifying costs and securing future funding. You can utilize the Analytics tab in Microsoft Copilot Studio to track these financial and performance metrics directly.

Calculating ROI with Copilot Studio Analytics The Analytics tab provides a dedicated Savings tile (ROI) that allows you to quantify the impact of your agents:

Define Savings Parameters: You can input estimated time saved (in seconds, minutes, or hours) and money saved per successful agent run.

Real-Time Tracking: Total savings are calculated automatically for your selected period based on successful runs of resolved conversations.

Retroactive Application: If you update your savings estimates, the system can apply these changes to previous runs to provide an accurate historical view.

Granular Insights: Savings can be defined at the overall agent-run level or for specific tools used within a run.

Deploy AI-powered business solutions - Question Set 3

QUESTION 1

You are designing a Microsoft Copilot Studio agent that uses a custom Microsoft Foundry model to generate responses.

You need to ensure that the agent can securely connect to and invoke the custom model during user interactions.

What should you include in the design?

A. Configure the agent to use classic orchestration.

B. Create a connection to Microsoft Foundry in the agent.

C. Add the Microsoft Foundry model as a Copilot Studio skill.

D. Create a custom engine agent.

—--

Correct Answer: B

Section: (none)

Explanation/Reference:

Explanation:

To create a connection to Microsoft Foundry within a Microsoft Copilot Studio agent and securely invoke a custom model, follow these steps:

1. Connect via the "External Agent" Method This method allows your Copilot Studio agent to orchestrate and call a specific Microsoft Foundry agent directly.

2. Connect via "Bring Your Own Model" (BYOM) If you want to use a specific model from the Foundry model catalog for individual prompt actions.

3. Security and Governance Connecting to Microsoft Foundry ensures enterprise-grade security through:

Entra ID Integration: Agents are assigned a unique Microsoft Entra Agent ID, allowing IT teams to enforce Conditional Access and Identity Governance.

Unified Management: Both your Copilot Studio and Foundry agents can be managed centrally in the Microsoft Entra admin center.

QUESTION 2

You are designing an AI business solution that contains the following components:

A Microsoft Power Automate workflow A Microsoft Copilot Studio agent A Microsoft Dataverse database A Microsoft Power Apps app

As part of the application lifecycle management (ALM) process, you plan to package the components, so that they can be deployed to other environments as a group.

You need to recommend a solution that supports versioning, dependencies, and deployments.

What should you include in the recommendation?

A. GitHub Actions

B. Azure DevOps

C. Microsoft Power Platform solutions

---

Correct Answer: C Section: (none)

Explanation/Reference:

Explanation:

To package your AI business solution components—including the Power Automate workflow, Copilot Studio agent, Dataverse database, and Power Apps app—you should use Microsoft Power Platform solutions.

While GitHub Actions and Azure DevOps are powerful tools for automating the deployment process (CI/ CD), Solutions are the actual "containers" or packaging mechanism required to bundle these specific Power Platform assets together so they can be moved as a single unit between environments.

QUESTION 3

A company has Microsoft 365 Copilot agents.

You need to design a security solution for the agents. The solution must meet the following requirements:

Identify and mitigate potential risks that relate to AI use.

Protect AI apps and the sensitive data processed or generated by the agents.

Support responsible AI governance by retaining and logging interactions, detecting policy violations, and investigating incidents.

Which two components should you include in the design? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Microsoft Purview

B. Azure AI Content Safety

C. role-based access control (RBAC) in Microsoft Foundry

D. Microsoft Defender

---

Section: (none)

Explanation/Reference:

Explanation:

To secure Microsoft 365 Copilot agents, you can implement a unified solution using Microsoft Purview for data governance and Microsoft Defender for real-time threat protection. This combination identifies risks, protects sensitive data, and ensures responsible AI governance through continuous monitoring and incident investigation.

QUESTION 4

You are creating validation criteria for a custom generative AI model that produces business reports based on internal enterprise data.

You need to assess whether the model's outputs are appropriate and meaningful for the business reports.

Which metric should you use?

A. the number of active users interacting with the model

B. alignment of the output to domain-specific tasks

C. the average system resource usage during inference

D. the model training duration

---

Correct Answer: B

Explanation/Reference:

Explanation:

To validate a custom generative AI model for business reports based on internal data, you should focus on alignment with domain-specific tasks through a mix of automated and human-centric metrics.

Validation Criteria for Business Reports *-> Task-Specific Quality Evaluation (TSQE): This is your primary metric for assessing whether outputs are meaningful for specific business tasks.

• Groundedness and Factuality: Measure the model's ability to provide information strictly referenced from your internal enterprise data. This prevents "hallucinations" that could lead to poor business decisions.

• Domain-Specific Benchmarking: Compare AI outputs against "ground truth" data—verified, accurate reports previously created by human experts.

QUESTION 5

A company has Microsoft Foundry agents that generate responses by using Azure OpenAI resources. The agents are deployed to both the United States and Europe.

A company mandate states that the agents and their grounding data must adhere to data residency and movement regulations.

You need to recommend a governance solution for the agents.

What should you include in the recommendation?

A. Microsoft Defender for Cloud

B. Azure Policy

C. Azure Monitor

D. Microsoft Purview

---

Correct Answer: D

Section: (none)

Explanation/Reference:

Explanation:

In this scenario, Microsoft Foundry agents and Azure OpenAI resources generate responses by using the Responses API. To ensure these agents adhere to data residency and movement regulations across the United States and Europe, Microsoft Purview should be included to provide the following governance and security controls:

Unified Data Discovery & Classification: Purview's discovery REST API allows orchestrator agents to identify relevant data assets (e.g., in Fabric or Databricks) across the organization's entire data landscape.

Sensitivity Label Enforcement: It ensures that AI-generated responses respect existing access controls by checking document label metadata at query time. This prevents oversharing of sensitive data and restricts users to authorized content.

Data Loss Prevention (DLP): By integrating Purview DLP policies, organizations can monitor, block, or warn when sensitive data is used in AI prompts or responses in real-time.

Data Residency Compliance: For strict European residency (e.g., GDPR), Azure OpenAI resources should be deployed using Data Zone (DZ) SKUs (such as in Sweden Central or Germany West Central), which contractually guarantee that both data storage and processing remain within the specified geography.

Embedded Governance: Admins can enable a native integration within Microsoft AI Foundry at the subscription level. This automatically sends prompt and response data to Purview for auditing and compliance without requiring additional developer code.

QUESTION 6

A company has a Microsoft Copilot Studio agent that uses custom connectors to interact with enterprise APIs.

You need to recommend an application lifecycle management (ALM) process to ensure that the connectors are deployed consistently across development, test, and production environments and meet governance and traceability requirements.

What should you recommend?

A. Deploy the APIs as Azure Functions.

B. Manage the connectors as solution components and deploy the components by using ALM pipelines.

C. Maintain connector definitions in environment variables.

D. Export and import the connectors between the environments as unmanaged solutions.

---

Correct Answer: C

Explanation/Reference:

Explanation:

To implement a robust Application Lifecycle Management (ALM) process for Microsoft Copilot Studio agents using custom connectors, you must leverage Solutions and Environment Variables to ensure consistency and governance.

1. Solution-Based Management

Always develop your custom connectors and Copilot Studio agents within a Power Platform Solution. This allows you to package all related components (connectors, environment variables, and agents) as a single unit for deployment across your ALM pipeline (Dev → Test → Prod).

1. Implementing Environment Variables

To maintain consistent definitions and meet governance requirements, externalize environment-specific values using Environment Variables:

Host and Base URL: Use environment variables for the API endpoint (e.g., api.dev.enterprise.com vs. api.prod.enterprise.com) to avoid manual edits during deployment.

Security Credentials: For OAuth settings like Client ID and Client Secret, use environment variables with the Secret data type.

Azure Key Vault Integration: For high-security enterprise APIs, store secrets in Azure Key Vault and reference them via secret environment variables to ensure traceability and governance.

UESTION 7

A company plans to implement an AI solution that will contain a Microsoft Copilot Studio agent and a Microsoft Foundry agent. The solution will be stored in a source code repository.

You need to recommend a deployment method for each agent. The solution must meet the following requirements:

A test environment must be used before a deployment to production. Production must be isolated from development and testing.

The deployment must be repeatable and fully automated.

The solution must NOT require manual intervention.

Which deployment method should you recommend for each agent? To answer, select the appropriate options in the answer area.

Answer Area

• Copilot Studio:

  • [ ] Export from the source code repository and import to the target environment.
  • [ ] Use a Bicep file.
  • [ ] Use a Microsoft Power Platform deployment pipeline.

• Microsoft Foundry:

  • [ ] Use a Bicep file.
  • [ ] Use a Microsoft Power Platform deployment pipeline.
  • [ ] Use an Azure DevOps pipeline.

---

Explanation/Reference:

Explanation:

Box 1: Use a Microsoft Power Platform deployment pipeline

Box 2: Use a Bicep file

Box 1: Use a Microsoft Power Platform deployment pipeline

Copilot Studio agent The preferred deployment method is to use a Microsoft Power Platform deployment pipeline.

Microsoft Power Platform pipelines are specifically designed to meet your requirements for a secure, automated, and repeatable application lifecycle management (ALM) process for Copilot Studio agents: Box 2: Use a Bicep file Microsoft Foundry agent In the scenario described for a Microsoft Foundry agent, the preferred deployment method is to use a Bicep file.

This approach is best suited for your requirements because:

Infrastructure as Code (IaC): Azure Bicep allows you to define your entire environment—including the Foundry hub, projects, and model deployments—as code stored in your source repository.

Automation & Repeatability: Bicep files integrate directly with GitHub Actions or Azure Pipelines, enabling fully automated, repeatable deployments without manual intervention.

Environment Isolation: You can use Bicep to provision distinct, isolated resources for development, testing, and production by parameterizing the deployment for each environment.

Suitability: While Power Platform pipelines are used for Copilot Studio agents, Foundry-based agents are Azure resources where Bicep is the native and more powerful automation tool for managing the underlying infrastructure and model endpoints

Box 2: Use a Bicep file

Microsoft Foundry agent

In the scenario described for a Microsoft Foundry agent, the preferred deployment method is to use a Bicep file.

This approach is best suited for your requirements because:

Infrastructure as Code (IaC): Azure Bicep allows you to define your entire environment—including the Foundry hub, projects, and model deployments—as code stored in your source repository.

Automation & Repeatability: Bicep files integrate directly with GitHub Actions or Azure Pipelines, enabling fully automated, repeatable deployments without manual intervention.

Environment Isolation: You can use Bicep to provision distinct, isolated resources for development, testing, and production by parameterizing the deployment for each environment.

Suitability: While Power Platform pipelines are used for Copilot Studio agents, Foundry-based agents are Azure resources where Bicep is the native and more powerful automation tool for managing the underlying infrastructure and model endpoints.

QUESTION 8

A company has a Microsoft Copilot Studio prompt-and-response agent. You need to ensure that the agent meets the following requirements:

Provides effective and relevant responses

Provides conversational outcomes Which metric should you use for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer Area

• Copilot Studio:

  • [ ] Export from the source code repository and import to the target environment.
  • [ ] Use a Bicep file.
  • [ ] Use a Microsoft Power Platform deployment pipeline.

• Microsoft Foundry:

  • [ ] Use a Bicep file.
  • [ ] Use a Microsoft Power Platform deployment pipeline.
  • [ ] Use an Azure DevOps pipeline.

---

Box 1: Generated answers rate and quality

Box 2: Satisfaction

Box 1: Generated answers rate and quality

Provides effective and relevant responses:

To ensure your Microsoft Copilot Studio agent provides effective and relevant responses, you should focus on the Generated Answer Rate and Quality metrics found in the Analytics dashboard. These metrics help you identify where the agent is succeeding and where knowledge gaps exist.

Key Quality Metrics Generated Answer Rate: Measures the frequency with which the agent successfully triggers a generative response from its knowledge sources.

Response Quality (Good vs. Poor): Copilot Studio automatically labels a sample of responses as "Good" or "Poor" quality based on AI assessment of relevance, completeness, and grounding.

Poor Quality Reasons: If a response is labeled "Poor," the system provides specific reasons, such as being incomplete, irrelevant, or not fully grounded.

Unanswered Questions: Tracks queries the agent could not answer, helping you identify missing documentation or topics.

Box 2: Satisfaction

Provides conversational outcomes

To ensure your Microsoft Copilot Studio prompt-and-response agent provides optimal conversational outcomes, you should use the Customer Satisfaction (CSAT) metric.

QUESTION 9

A company extends Copilot in Microsoft Dynamics 365 Customer Service.

You need to recommend an automated application lifecycle management (ALM) process so that the Copilot components can be safely developed, tested, and promoted to production.

Which two actions should you include in the ALM process? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Use an unmanaged solution in production.

B. Rebuild the agents in each environment.

C. Use Microsoft Power Platform pipelines.

D. Include the components in a solution.

E. Store the agent transcripts in source control.

---

Correct Answer: CD Section: (none)

Explanation/Reference:

Explanation:

To implement an automated Application Lifecycle Management (ALM) process for extending Microsoft Dynamics 365 Customer Service with Copilot, you should leverage Power Platform solutions and pipelines. This approach ensures that custom agents, knowledge sources, and connector actions are developed and promoted safely across environments.

Tools used include:

Power Platform Pipelines: Automates the deployment process across environments.

To automate the application lifecycle management (ALM) for Copilot components within Microsoft Dynamics 365 Customer Service, follow this structured process using Power Platform pipelines and solutions:

1. Solution-Centric Development

All Copilot components (agents, topics, custom actions, and connector plugins) must be developed within a Power Platform solution.

Create or Select a Solution: In Copilot Studio or the Power Apps maker portal, ensure you are working within an unmanaged solution in your Development environment.

Add Components: When you create new agents or actions in Microsoft Copilot Studio, they are automatically associated with the preferred solution you have set, ensuring they are portable.

1. Pipeline Configuration

Power Platform pipelines democratize ALM by providing a built-in CI/CD experience directly within the maker portal.

Incorrect:

[Not A] Use Managed Solutions for Production: Export and deploy solutions as managed when promoting to test or production environments to prevent unauthorized direct changes in those environments and ensure a consistent state.

QUESTION 10

You are designing a testing solution for a Microsoft Copilot Studio agent that integrates with Microsoft Dynamics 365 Customer Service and Dynamics 365 Sales.

You need to design end-to-end scenarios to test the agent's ability to perform the following actions:

• Coordinate tasks and data interactions across both Dynamics 365 apps.
• Interpret user input and provide contextually relevant outputs.

Which test scenario and metric should you include in the design? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

• Copilot Studio:

  • [ ] Export from the source code repository and import to the target environment.
  • [ ] Use a Bicep file.
  • [ ] Use a Microsoft Power Platform deployment pipeline.

• Microsoft Foundry:

  • [ ] Use a Bicep file.
  • [ ] Use a Microsoft Power Platform deployment pipeline.
  • [ ] Use an Azure DevOps pipeline.

---

Box 1: Run task-based scenarios that involve both apps

Box 2: Track the successful completion of cross-app tasks

Box 1: Run task-based scenarios that involve both apps

Test scenario

Task-Based Testing Scenarios Run these end-to-end scenarios to verify the agent's ability to interpret context and coordinate data: Scenario 1: Cross-Sell Opportunity Discovery Task: While resolving a support case in Customer Service, ask the agent: "Are there any active sales opportunities for this account?".

Success Criteria: The agent retrieves the relevant Opportunity from Sales, summarizes it, and suggests a follow-up action for the sales team.

Scenario 2: Integrated Case/Lead Creation Task: A user mentions a new product interest during a support chat. Command the agent: "Create a lead in Sales based on this support conversation".

Success Criteria: The agent parses the conversation history and creates a Lead record in Sales with the correct customer context.

Scenario 3: Proactive Account Health Check Task:

Before a sales meeting, ask: "Summarize recent support issues for this account".

Success Criteria: The agent identifies open tickets in Customer Service and provides a summary to the Sales professional to prevent walking into a "blind" meeting.

Box 2: Track the successful completion of cross-app tasks Metric

Key Metrics for Success Track these specific metrics in the Copilot Studio Analytics tab or the Power Platform Admin Center:

*-> Resolution Rate (Cross-App): The percentage of sessions where the agent successfully completed a task requiring data from both apps without manual intervention.

Deflection Rate: Reduction in human handoffs for tasks that previously required an agent to switch manually between Sales and Service hubs.

Task Success Threshold: Define a minimum quality score for LLM-based responses to ensure the context provided from the "other" app is accurate.

Agent Assisted Hours Gained: Measure the time saved by the agent performing these cross-app queries versus a human doing so manually.

QUESTION 11

A company has multiple AI models that support generation of sales transactions.

Each release of the models must be reviewed by a security and compliance team before being deployed to the production environment. The security and compliance team must have access to prior versions to properly determine potential exposures introduced.

You need to recommend a solution to evaluate the impact of each deployment to production. The solution must enhance business continuity.

What should you recommend?

A. Create a central model registry that uses version history.

B. Establish a promotion process by using a quality gate.

C. Implement version control for all the AI system components.

D. Track model retirement schedules to prevent service disruptions.

---

Correct Answer: C

Explanation/Reference:

Explanation:

To ensure business continuity and minimize risks in AI-driven sales transaction systems, implementing comprehensive version control across all system components is a critical requirement. This provides reviewers with a stable baseline to evaluate new releases against older versions, helping identify potential exposures or regressions before they reach production.

Strategic Implementation for AI Version Control Version All Components: Do not limit version control to application code. You must track: *-> Models: Managed iterations including weights and architecture.

Etc.

Benefits for Business Continuity Predictability: Standardized versioning makes AI behavior more auditable and scalable.

Disaster Recovery: Allows teams to quickly reproduce or restore any previous environment state during a failure.

Regulatory Compliance: Provides the necessary evidence of "what the AI was instructed to do" at any given point, which is mandatory for regulated financial environments.

QUESTION 12

A company has an AI solution that uses a Microsoft Copilot Studio agent.

You need to monitor the agent's performance. The solution must meet the following requirements:

• Monitor the agent's telemetry in near-real-time (NRT).
• Download transcripts of full conversations.
• Monitor the agent's usage and performance.

What should you use for each requirement? To answer, drag the appropriate options to the correct requirements. Each option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Options

• Application Insights
• Copilot Studio
• Log Analytics
• Microsoft Power Apps

Answer Area

• Monitor the agent's telemetry in NRT:
• Download transcripts of full conversations:
• Monitor the agent's usage and performance:

Options

---

Box 1: Application Insights

Box 2: Microsoft Power Apps

**Box 1: Application Insights **

Monitor the agent's telemetry in near-real-time (NRT).

To monitor Microsoft Copilot Studio agent performance and telemetry in near-real-time (NRT), the best tool to use is Azure Application Insights.

By connecting your Copilot Studio agent to an Azure Application Insights instance, you can capture detailed runtime data, including user messages, topics triggered, and custom events as they happen.

Box 2: Microsoft Power Apps

Download transcripts of full conversations.

To monitor Microsoft Copilot Studio agent performance, you can download full conversation transcripts for the last 29 days using the Power Apps portal to analyze user interactions. Access Dataverse via Power Apps, navigate to tables, select ConversationTranscript, and export the data as a CSV file to identify engagement, resolution, and escalation patterns.

Steps to Download Transcripts via Power Apps:

1. Sign in to make.powerapps.com.

2. Select the correct environment in the top right corner.

3. In the side menu, select Tables (or Data > Entities in older views).

4. Search for and select the ConversationTranscript table.

5. Select Export data from the top menu.

6. Once compiled, select Download exported data to save the file.

Box 3: Copilot Studio

Monitor the agent's usage and performance.

To monitor a Microsoft Copilot Studio agent's usage and performance, you can use the built-in Analytics page in Copilot Studio, which provides comprehensive data on key metrics, conversation outcomes, and user satisfaction.

QUESTION 13

A company deploys a Microsoft Copilot Studio agent that integrates with a Microsoft Power Automate desktop flow.

You need to recommend a testing solution that meets the following requirements:

Test cases must validate the most recent changes to the agent before the agent is released.

The flow must be validated as part of the agent's orchestration.

What should you recommend for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

Answer Area

Validate the most recent changes to the agent before release:

• Publish the agent to a channel and test the agent on live users.
• Run tests against the latest unpublished version of the agent.
• Run tests against the production version of the agent.

Validate the flow as part of the agent's orchestration:

• Add the flow to the agent as a tool.
• Add the flow to a canvas app.
• Use the Power Automate for desktop console.

---

Box 1: Run test against the latest unpublished version of the agent

Box 2: Use the Power Automate for desktop console

The flow must be validated as part of the agent's orchestration.

To ensure your Microsoft Power Automate desktop flow is correctly validated for orchestration within a Microsoft Copilot Studio agent, follow these steps using the Power Automate for desktop console and the Copilot Studio designer:

1. Validate via Power Automate for Desktop Console

Run a Local Test: Open the Power Automate for desktop console, select your flow, and click the Start button to run it as a "local attended" flow. This confirms that the logic and UI selectors work correctly in your environment.

Check Variables: Ensure that any Input and Output variables are properly defined. These are critical for passing data between the cloud-based agent and the desktop machine.

Monitor Connectivity: Use the Troubleshooter within the console (under Help > Troubleshooter) to diagnose any connectivity issues with the cloud runtime, ensuring the agent can trigger the desktop flow.

1. Validate the Integration in Copilot Studio

QUESTION 14

A company has a Microsoft Copilot Studio agent that provides answers based on a knowledge base for customer support.

Users report that, occasionally, the agent provides inaccurate answers.

You need to use metrics from the Analytics tab in Copilot Studio to identify the cause of the inaccuracies.

Which two options should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. survey results

B. session information and session outcomes

C. topic usage and topics with low resolution

D. engagement, resolution, and escalation rates

E. quality of generated answers

---

Correct Answer: CD

Explanation/Reference:

Explanation:

[C] You can use the Analytics dashboard to identify and fix inaccurate responses by focusing on specific performance signals:

*-> Topics with Low Resolution: This metric identifies individual topics where sessions frequently end without a successful outcome. A low resolution rate often indicates that the topic's logic is flawed, the content is outdated, or it fails to address the user's specific intent.

*-> Topic Usage: High usage of certain topics combined with low resolution or high escalation rates points to critical knowledge gaps. Use this to prioritize which parts of your knowledge base need immediate refinement.

Unrecognized Utterances: Review these to find user phrases that didn't trigger any custom topic, indicating missing content or the need for new trigger phrases.

Analyze User Questions by Theme: Copilot Studio uses AI to group generative responses into themes. You can review these clusters to see which themes have poor response quality and need better grounding or data hygiene.

User Feedback (Thumbs Up/Down): Review specific messages with negative feedback in the Analytics tab to understand exactly where the AI is hallucinating or providing incomplete data.

[D] In Microsoft Copilot Studio, you can use analytics to pinpoint why your agent is providing inaccurate answers by following a structured improvement checklist.

Using Metrics to Locate Problems *-> Engagement Rate: A low engagement rate often indicates that your triggers are misconfigured or too broad, causing the agent to initiate the wrong topic or fail to recognize user intent entirely.

*-> Resolution Rate: Identify specific topics with low resolution. If a topic has a high volume of sessions but fails to reach a "Resolved" state, it usually means the knowledge source is outdated, mismatched, or the generative answers are not grounded properly.

*-> Escalation Rate: High escalation rates for particular topics are "red flag" drivers. Use the Escalation Rate Drivers chart to see which topics most frequently force a hand-off to a human agent, indicating where the AI's knowledge or logic is insufficient.

Incorrect:

[Not B] To locate and resolve inaccuracies in your Microsoft Copilot Studio agent, you can leverage the Analytics tab to examine session data and outcomes.

1. Use Session Outcomes to Identify Failure Points The Analytics dashboard categorizes "Engaged" [D] sessions into three primary outcomes that highlight where the agent is failing:

Escalated: These sessions reached the "Escalate" [D] system topic or a "Transfer Conversation" node. High escalation rates for specific topics often indicate that the knowledge base lacks the depth to answer those queries.

Abandoned: These sessions ended without being resolved or escalated [D]. This often happens when users get frustrated by repetitive or inaccurate answers and close the chat.

Resolved [D]: These are successful sessions. If a session is marked Resolved (Confirmed), the user explicitly verified the answer was helpful. If it is Resolved (Implied), the agent assumed success because the user didn't ask further questions, which can sometimes mask inaccuracies.

QUESTION 15

A company uses a fine-tuned Microsoft Foundry model that requires frequent updates as new customer feedback becomes available.

You need to design an application lifecycle management (ALM) process that meets the following requirements:

Data changes must be tracked and versioned.

The model must be retrained consistently by using approved training data.

Which two actions should you include in the design? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Associate the storage location to the fine-tuning job.

B. Create a content filter.

C. Store the training data in Azure Files.

D. Upload the training data to Microsoft Foundry data files

E. Store the training data in Azure Blob Storage that has version control enabled.

---

Correct Answer: DE Section: (none)

Explanation/Reference:

Explanation:

To implement a new Application Lifecycle Management (ALM) process for your fine-tuned Microsoft Foundry model, you can leverage Azure Blob Storage for raw data versioning and Azure AI Foundry (formerly Azure AI Studio) for managed data assets and model retraining.

1. Data Tracking and Versioning in Azure Blob Storage Enable blob versioning to automatically maintain a history of your training data.

Enable Versioning: In the Azure portal, navigate to your storage account under Data management > Data protection and select Enable versioning for blobs.

Immutable Tracking: This ensures that every update to a training file creates a new version, allowing you to restore or reference specific historical states of your dataset for auditability.

1. Uploading and Managing Data in Microsoft Foundry Integrate your versioned blob storage with Microsoft Foundry to create "Data assets" that the model can use for retraining.

Reference:

QUESTION 16

A company deploys agents that generate responses by using Azure OpenAI resources. The agents are deployed to both the United States and Europe.

You need to recommend a governance solution that meets the following requirements:

Enforces the deployment of the resources to only approved Azure regions Provides continuous compliance verification of the resources

What should you include in the recommendation for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

Answer Area

Enforces the deployment of the resources to only approved regions:

• Azure Monitor
• Azure Policy
• Microsoft Defender for Cloud
• Microsoft Purview
• Microsoft Sentinel

Provides continuous compliance verification of the resources:

• Azure Monitor
• Azure Policy
• Microsoft Defender for Cloud
• Microsoft Purview

---

Box 1: Azure Policy

Box 2: Microsoft Purview

Box 1: Azure Policy

Enforces the deployment of the resources to only approved Azure regions To enforce the deployment of Azure OpenAI resources to only approved Azure regions (e.g., specific regions in Europe and the USA), you should use Azure Policy with the "Allowed locations" policy definition.

Here is the breakdown of how to implement this control:

Primary Tool: Azure Policy Azure Policy allows you to define rules that restrict where resources can be created.

Policy Rule: Use the Allowed locations policy definition.

Implementation: Assign this policy at the Subscription or Resource Group level to restrict developers to only using permitted regions (e.g., East US, West Europe).

Effect: If a user attempts to deploy an Azure OpenAI resource in a non-approved region, the deployment will be blocked.

Box 2: Microsoft Purview

Provides continuous compliance verification of the resources To provide continuous compliance verification for Azure OpenAI resources across Europe and the USA, you should use Microsoft Purview Compliance Manager and Azure Policy.

Microsoft Purview Compliance Manager: This tool provides a risk-based compliance score and continuous monitoring against global regulations such as the EU AI Act, GDPR, and various US standards. It offers specific regulatory templates to help you assess and implement controls for generative AI applications. Azure Policy: Use this to enforce organizational standards and assess compliance at scale. You can apply built-in policy definitions for Azure AI services to automatically audit or deny non-compliant resource configurations, such as ensuring resources are restricted to specific regions (e.g., only EU or USA) or have private network access enabled.

QUESTION 17

A company has an AI solution that uses Azure OpenAI models.

You need to recommend a governance solution that monitors and audits changes to model configurations and data usage. The solution must minimize administrative effort.

What should you include in the recommendation?

A. Azure Monitor

B. Azure Stream Analytics

C. Azure API Management

D. Azure Policy

E. Microsoft Purview

---

Correct Answer: A Section: (none) Explanation/Reference:

Explanation:

Azure Monitor is the primary service for monitoring and auditing Azure OpenAI model configurations and data usage. By combining Azure Monitor with diagnostic settings, you can track management operations, analyze token consumption, and audit prompt/response data.

QUESTION 18

A company uses Azure OpenAI models that use grounding data from Microsoft Fabric for agents. The models are fine-tuned by using proprietary datasets.

You need to design a governance solution that meets the following requirements:

Restricts access to the grounding data to only assigned roles Restricts model fine-tuning to only the AI engineering team What should you include in the design? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Answer Area

Restricts access to the grounding data:

• Azure AI Content Safety
• Azure Monitor alerts
• Azure Policy compliance rules
• Microsoft Purview access policies

Restricts model fine-tuning:

• Azure Policy compliance rules
• Azure Resource Manager (ARM) resource locks
• Microsoft Entra Conditional Access
• Role-based access control (RBAC) in Microsoft Foundry

Explanation/Reference:

Explanation:

Box 1: Microsoft Purview Access Policies Restricts access to the grounding data to only assigned roles

To secure and manage grounding data from Microsoft Fabric for Azure OpenAI agents and fine-tuned models, you can use Microsoft Purview to enforce role-based access and data protection policies.

Note:

Securing Data with Microsoft Purview & RBAC

Access Control Policies: Microsoft Purview enables role-based access controls (RBAC) over Fabric items, ensuring that when an AI agent retrieves data, it only accesses information the user is permitted to see.

Sensitivity Labels: Data in Fabric can be labeled (e.g., "Confidential"). Purview policies can restrict AI agents from accessing or acting upon content that violates these security labels.

OneLake Security: Fine-grained security in Fabric (Row-Level Security and Column-Level Security) is automatically honored by agents, guaranteeing that even with access to a dataset, sensitive PII (Personally Identifiable Information) can be restricted.

Incorrect:

• Azure AI Content safety

You cannot use Azure AI Content Safety to restrict access to grounding data based on assigned roles. Azure AI Content Safety is used for content filtering (detecting harmful text/images, jailbreak attempts, and ungroundedness/hallucinations).

• Azure Policy compliance rules.

Azure Policy can be used to enforce compliance rules, such as restricting model deployments to specific regions or ensuring private networking is used.

Box 2: Role-based access control (RBAC) in Microsoft Foundry Restricts model fine-tuning to only the AI engineering team

Azure role-based access control (Azure RBAC) is used to manage and restrict access to AI resources, including the ability to perform fine-tuning operations. Platform administrators can assign specific roles and permissions (e.g., to AI engineers or data scientists) and use Azure Policy to implement fine-grained control over who can initiate fine-tuning jobs or deploy custom models within the Azure AI Foundry environment. This ensures the governance of the fine-tuning process.

QUESTION 19

A company has a Microsoft Copilot Studio agent that has been in production for three months.

The agent has received positive feedback from users.

You need to identify the number of questions unanswered by the agent and the number of abandoned sessions between the users and the agent.

Which Copilot Studio insights should you use? To answer, drag the appropriate insights to the correct requirements. Each insight may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Select and Place:

Insights

• Conversation outcomes
• Generated answer rate and quality
• Reactions
• Survey results

Answer Area

• The number of unanswered questions:
• The number of abandoned sessions:

Insight

---

Explanation/Reference:

Explanation:

Box 1: Generated answer, rate and quality

The number of questions unanswered

In Microsoft Copilot Studio, you can find the number of unanswered questions by navigating to the Analytics page and viewing the Generated answer rate and quality section.

This specific analytics area provides insights into how often the agent successfully generates a response versus when it fails to do so.

Box 2: Conversation outcomes

The number of abandoned sessions between the users and the agent

To find the number of abandoned sessions in a Microsoft Copilot Studio agent's analytics, you can use the Conversation outcomes chart within the Analytics dashboard.

This chart specifically tracks and visualizes sessions with an "Abandoned" outcome.

QUESTION 20

You are evaluating a Microsoft Copilot Studio agent that supports Microsoft Dynamics 365 Customer Service representatives.

You need to recommend a testing solution that meets the following requirements:

Evaluates agent effectiveness during active sessions Validates whether the agent delivers accurate and helpful responses Provides measurable, actionable insights for continuous improvement

What should you recommend?

A. Track resolution, deflection, and accuracy by using dashboards and use scripts to ensure consistent responses.

B. Perform load testing to validate how the agent scales under a high chat volume.

C. Review historical tickets to find agents that have the shortest resolution times.

D. Measure uptime and page load times.

---

Correct Answer: A

Explanation/Reference:

Explanation:

To establish a testing and evaluation setup for your Microsoft Copilot Studio agent within Dynamics 365 Customer Service, you should leverage specialized AI-driven evaluation agents and integrated analytics dashboards.

1. Evaluate Effectiveness and Accuracy Use the Quality Evaluation Agent in Dynamics 365 to automate the assessment of agent performance during and after active sessions.

2. Track Measurable Insights with Dashboards Utilize the built-in and customizable dashboards to monitor key performance indicators (KPIs) like resolution and deflection.

3. Ensure Consistency with Agent Scripts To maintain uniform and company-endorsed communication, implement Agent Scripts within the Customer Service Admin center.

QUESTION 21

A company uses multiple Microsoft Copilot Studio agents across different channels.

You need to recommend a monitoring solution that provides comprehensive telemetry data and performance insights for the agents.

What should you include in the recommendation?

A. Application Insights

B. Azure Advisor

C. Azure DevOps

D. Microsoft Dynamics 365 Customer Voice

---

Correct Answer: A Section: (none)

Explanation/Reference:

Explanation:

To achieve comprehensive monitoring, telemetry, and performance insights for Microsoft Copilot Studio agents across different channels, you should integrate them with Azure Application Insights.

Integrating Application Insights provides a centralized view of agent health, user interactions, topic performance, and latency, which is crucial for monitoring multi-channel deployments.

QUESTION 22

A company has an AI solution built by using Microsoft Copilot Studio and Power Platform. The solution is used by the company's sales, marketing, and customer service teams.

You are performing a return on AI investment (ROAI) analysis to evaluate the impact of the solution.

You need to identify which measurable business drivers to include in the analysis.

Which two business drivers should you identify? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. the reduced average case resolution time

B. market capitalization

C. economic market predictability

D. increased employee productivity

E. brand awareness

---

Correct Answer: AD Section: (none)

Explanation/Reference:

Explanation:

[A] Reducing the average case resolution time is a high-impact, measurable business driver for an AI investment (ROAI) analysis, particularly when implementing Microsoft Copilot Studio and Power Platform for local sales, marketing, and customer service teams.

According to Microsoft and industry research, this metric directly translates to reduced operational costs, increased agent productivity, and higher customer satisfaction.

[D] Increased employee productivity is a primary and highly measurable business driver for an AI investment (ROAI) analysis involving Microsoft Copilot Studio and Power Platform, particularly for sales, marketing, and customer service teams. These tools allow organizations to automate manual tasks, streamline workflows, and enhance content generation, directly resulting in time savings and efficiency gains.

Incorrect:

[Not B] While market capitalization is a macro-level indicator that reflects investor confidence in a company's AI maturity, it is generally not considered a direct, measurable business driver for a specific internal project's Return on AI Investment (ROAI). Market cap is influenced by many external factors beyond a single implementation of Microsoft Copilot Studio or Power Platform.

QUESTION 23

A company has a Microsoft Foundry agent that summarizes customer feedback and recommends products to customers. The agent references data from multiple knowledge sources.

Users report that the agent response time is slow.

Telemetry data shows that the agent frequently reaches its token usage limit.

You need to recommend a solution to reduce token usage without degrading the quality of the generated responses.

What should you recommend?

A. Chunk documents during indexing.

B. Reduce the number of knowledge sources used by the agent.

C. Reconfigure the prompts to limit the amount of retrieved content from the knowledge sources.

D. Lower the maximum token usage limit for the responses.

---

Correct Answer: C Section: (none)

Explanation/Reference:

Explanation:

To reduce token usage and improve performance in a Microsoft Foundry agent with slow response times and high token usage, reconfigure the prompts to limit the amount of retrieved content from the knowledge sources. This directly reduces the input token count in the prompt, addressing the bottleneck without removing valuable sources.

To reduce token usage while maintaining quality, you must transition from a "wide-net" retrieval strategy to a highly filtered, multi-stage retrieval process. The goal is to ensure that every token entering the prompt adds unique, high-value information.

The Root Cause Redundancy: Multiple knowledge sources often contain overlapping feedback.

Noise: Raw data often includes metadata or conversational filler.

Context Bloat: Large retrieval windows push the agent toward its limit and slow down processing.

QUESTION 24

A company has Microsoft Power Platform development, staging, and production environments. Each environment has its own Microsoft Dataverse tables and Azure AI Search index.

You are designing an application lifecycle management (AIM) process to deploy a Microsoft Copilot Studio agent between the environments.

The company has a Copilot Studio agent named Agent1 in development. Agent1 uses the following grounding data sources:

A Dataverse table named CustomerOrders An Azure AI Search index named customer-knowledge

You need to deploy Agent1 to production. The solution must ensure that the agent uses the production grounding data sources, minimizes downtime, and handles credentials and endpoints securely.

What should you include in the deployment package solution, and what should you reconfigure after the deployment? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Include in the deployment package solution:

• Agent1 only
• The data sources only
• Agent1 and the data source connections
• Agent1 and references to the data sources
• Agent1, the data sources, and the data source connections

Reconfigure after the deployment:

• The Dataverse connection only
• The Azure AI Search connection only
• The Dataverse and Azure AI Search connections
• The Agent1 configuration
• The environment variables

---

Box 1: Agent1 and references to the data sources

Box 2: The environment variables

Box 1: Agent1 and references to the data sources

Include in the deployment package solution

To deploy a Microsoft Copilot Studio agent with Dataverse and Azure AI Search dependencies across environments, you must use a Managed Solution as your primary deployment package. This ensures environment-specific configurations are handled without hardcoding, maintaining security and minimizing downtime.

Key Components of the Deployment Package Your solution package must include the following components to ensure a seamless transition between development, staging, and production:

*-> Copilot Studio Agent: The core bot configuration and its topics.

*-> Connection References: Placeholders that link the agent to specific connectors (e.g., Azure AI Search, Dataverse) in each environment.

Environment Variables: Used to store the Azure AI Search Endpoint URL and Index Name. Dataverse Table Metadata: If using custom tables, include the table definitions (schema) within the solution.

Power Automate Flows: If flows are used to bridge the agent and search index, they must be included in the same solution.

Box 2: The environment variables

Reconfigure after the deployment

To successfully deploy a Copilot Studio agent across environments while maintaining the integrity of its data grounding, you must reconfigure the Connection References and Environment Variables within the target environment.

In a professional ALM (Application Lifecycle Management) pipeline, you should not manually "edit" the agent after deployment. Instead, the solution should be designed to use placeholders that are updated during the import process.

Update Environment Variables Purpose: Swaps out API endpoints and resource names.

Action: Provide the production values for:

Azure AI Search Endpoint: (e.g., https://windows.net) Index Name: The specific name of the production index.

API Keys: Ideally stored in Azure Key Vault and referenced via an environment variable.

Benefit: Allows the same agent logic to run in any environment by simply changing the variable values

QUESTION 25

A company has a Microsoft Copilot Studio agent that uses generative AI to assist Microsoft Dynamics 365 Customer Service representatives.

The agent currently exhibits a low resolution rate and a high escalation rate.

You need to identify the issue.

What should you use?

A. the Agent dashboard of Dynamics 365 Customer Service historical analytics

B. the Insights tab from the Search & intelligence settings of the Microsoft 365 admin center

C. the Copilot hub in the Power Platform admin center

D. the Analytics tab in Copilot Studio

---

Correct Answer: D Section: (none)

Explanation/Reference:

Explanation:

To locate the problem behind a low resolution and high escalation rate in your Copilot Studio agent, you should focus on a multi-layered diagnostic approach. High escalation typically signals that the agent is hitting a "Fallback" trigger or failing to find grounded answers in its knowledge base.

Core Diagnostic Steps Analyze Analytics Dashboards *-> Use the built-in Copilot Studio Analytics tab to identify high-level trends.

Escalation Rate Drivers: Look for the top 5–10 topics causing escalations. Improving these key topics by even 10% can significantly boost overall deflection

Outcome Reason: Check the outcomeReason in the ConversationTranscript table in Dataverse to see if sessions end due to abandonment, system errors, or explicit user requests for a human.

QUESTION 26

A company has a Microsoft Foundry generative AI model.

You need to evaluate the model's output to measure the overall quality and coherence of generated responses. The evaluation must use GPT-4o as a judge and return a numeric score for each output. Which type of metric should you use?

A. AI quality (NLP)

B. risk and safety

C. Groundedness

D. AI quality (AI assisted) Correct Answer: D Section: (none) Explanation/Reference:

Explanation:

To evaluate overall quality and coherence in Microsoft Foundry, use AI-assisted quality evaluators. These metrics use a "judge" model (like GPT-4o) to score responses on a numeric Likert scale (typically 1 to 5). Recommended Metric: Coherence The Coherence evaluator is the most direct fit for measuring how well-structured and logical a response is.

What it measures: The collective quality of all sentences and how they flow together.

Numeric Score: Returns an integer from 1 (Poor) to 5 (Excellent).

Output: Includes a coherence score, a coherence_reason (explanation from the judge), and a pass/fail result based on a threshold (default is 3).

QUESTION 27

You use Microsoft Copilot Studio analytics to analyze the performance of a deployed Copilot Studio agent.

You need to identify which performance metrics to use to measure the following:

• The percentage of engaged sessions that are escalated to a live customer service representative

• The number of agent queries that cause a knowledge source error What should you identify for each requirement?

To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

The percentage of engaged sessions that are escalated to a representative:

• Answer quality
• Customer Satisfaction (CSAT) score
• Engagement rate
• Escalation rate

The number of agent queries that cause a knowledge source error:

• Answer quality
• Engagement rate
• Escalation rate

---

Box 1: Escalation rate

Box 2: Answer quality

Box 1: Escalation rate

The percentage of engaged sessions that are escalated to a live customer service representative To measure the percentage of engaged sessions that are escalated to a live customer service representative in Microsoft Copilot Studio analytics, you should use the Escalation rate metric.

Lowering this percentage is a key objective to improve the overall deflection rate and enhance agent performance.

Definition: An escalated session is an engaged session that ends when the Escalate topic is triggered, or when a Transfer to agent node is reached.

Context: This metric helps you understand the proportion of users who requested to speak to a human or were passed to a representative because the agent couldn't solve their issue.

Where to find it: It is available in the Analytics dashboard within Copilot Studio, specifically under "Escalation Rate Drivers" which shows which topics cause the most escalations.

Box 2: Answer quality

The number of agent queries that cause a knowledge source error When analyzing Microsoft Copilot Studio agent performance, the answer quality performance metric should be used to measure queries that cause a knowledge source error. This AI-driven metric assesses if responses are grounded in provided knowledge, helping to identify, evaluate, and reduce errors in generative answers.

Key Aspects of Copilot Studio Analytics:

Answer Quality: Utilizes Large Language Models (LLMs) to categorize chat messages, focusing on grounding, relevance, and accuracy.

Explanation/Reference:

Explanation:

To implement an Application Lifecycle Management (ALM) process for Microsoft Foundry agent deployment, you must integrate Foundry Control Plane Observability into your CI/CD pipeline. This ensures the agent is validated against baseline metrics before reaching production and monitored for drift thereafter.

Pre-Deployment: Baseline Evaluation Before a new agent version is deployed, it must pass a rigorous evaluation stage within your ALM pipeline to prevent performance regressions.

Post-Deployment: Drift & Continuous Monitoring Once deployed, the agent’s performance must be continuously validated against the pre-deployment baseline using Observability in the Control Plane.

Continuous Evaluation: Configure the Control Plane to sample live production traffic and run the same evaluators used during development.

Drift Detection: Monitor for changes in Quality Scores and Accuracy Metrics over time. Significant drops indicate "drift," where real-world usage differs from your training/testing assumptions.

Unified Dashboard: Use the Foundry Monitoring Dashboard to visualize trends in latency, token usage, and accuracy side-by-side.

Alerting: Set up Azure Monitor alerts to notify developers immediately if evaluation scores fall below the established baseline.

QUESTION 29

You need to recommend a security solution for agents in a Microsoft Power Platform environment.

The agents must use only approved connectors and services. The solution must prevent the agents from accessing sensitive data.

What should you recommend?

A. Configure Azure Monitor to capture connector activity logs.

B. Enable a Microsoft Dataverse audit.

C. Deploy data loss prevention (DLP) policies in Power Platform.

D. Enable customer-managed keys in Microsoft Dataverse.

---

Correct Answer: C Section: (none)

Explanation/Reference:

Explanation:

To secure Microsoft Power Platform agents, deploy DLP policies via the Power Platform Admin Center to categorize connectors as Business, Non-business, or Blocked. This prevents unauthorized data exfiltration by separating sensitive connectors and restricting approved services, ensuring agents only use compliant actions.

Note Key Actions for Agent DLP Policies:

Create Policy: Create a new policy in the Power Platform Admin Center and define its scope.

Categorize Connectors: Classify connectors used by agents (e.g., HTTP, SQL) into Business/Nonbusiness to prevent data sharing between them.

Block High-Risk Connectors: Block unauthorized or risky connectors (e.g., public social media, unapproved AI tools).

Configure Endpoint Filtering: Block specific URLs for HTTP connectors to ensure data only travels to trusted domains.

Apply to Agents: According to Platforms of Power, specific connectors for Copilot Studio can be blocked to limit agent capabilities, such as preventing autonomous triggers.

Quarantine Agents: If agents violate Microsoft Learn policies, 365 Copilot Studio allows quarantining the agents to prevent further data exposure.

QUESTION 30

A company has an AI business solution that uses Microsoft Copilot Studio agents.

You need to recommend prompt best practices to improve the effectiveness of agent interactions.

Which two actions should you include in the recommendation? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Track the duration of the average user session.

B. Analyze the prompt length distribution.

C. Regularly test and refine the prompts based on user input.

D. Use clear and specific instructions in the prompts.

E. Measure system resource usage during prompt processing.

---

Correct Answer: CD

Explanation/Reference:

Explanation:

To maximize the effectiveness of Microsoft Copilot Studio agents through prompt engineering, the two best practices you mentioned are critical, along with several key refinements:

1. Use Clear and Specific Instructions in Prompts

Define Goal, Context, and Persona: Provide a clear objective (what to do), necessary context (background information), and a defined persona (e.g., "You are an HR assistant...") to set the tone.

Be Specific and Actionable: Use precise verbs like "search," "summarize," "draft," or "list." Avoid vague instructions. For example, instead of "tell me about sales," use "Summarize Q3 sales performance in the North region".

Use Structured Formats: Utilize Markdown (headings, bullet points, numbered lists) to make instructions easy to scan and parse. Organize instructions into sections like # PURPOSE, ## RESTRICTIONS, and ## ACTIONS.

Provide Examples (Few-Shot Prompting): Include examples of inputs and desired outputs to help the agent understand complex tasks or required formatting.

Define Constraints: Explicitly state what the agent should not do, what information to exclude, or when to decline a request.

1. Regularly Test and Refine Prompts Based on User Input

Test within Copilot Studio: Utilize the testing pane to simulate user queries and review agent responses. Experiment with different prompt variations to see which yields the best result.

Use Prompt Advisor: Leverage the Prompt Advisor feature to get a confidence score and feedback on your prompts, which helps identify areas for improvement.

Review Analytics: Regularly check conversation logs, customer feedback (thumbs up/down), and user queries in the analytics dashboard to find where the agent struggles.

Iterate and Improve: Treat prompting as a conversation with the agent. If the first output isn't perfect, refine the instructions, add more context, and try again.

Monitor Performance (Red Teaming): Test edge cases and potential failure modes to ensure the agent remains reliable and secure.

By following these practices, you can make agent behavior more predictable, accurate, and useful for end-users

QUESTION 31

A company has a cloud-based AI solution that uses Azure OpenAI models.

You need to design a monitoring solution that meets the following requirements:

Monitors performance metrics and operational health for the models

Monitors AI apps and agents for compliance

Uses Azure-native capabilities

Minimizes development effort What should you use for each requirement? To answer, drag the appropriate options to the correct requirements. Each option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Select and Place:

Options

• Azure API Management
• Azure Policy
• Microsoft Defender
• Azure Monitor
• Azure Stream Analytics
• Microsoft Purview

Answer Area

Monitors AI app and agents for compliance: [______]

Monitors performance metrics and operational health: [______]

---

Explanation/Reference:

Explanation:

Box 1: Microsoft Purview Monitors

AI apps and agents for compliance

To monitor Azure OpenAI models and agents for compliance with minimal effort, you can leverage Microsoft Purview through its native integration with Azure AI Foundry. This "turn-key" approach allows security administrators to capture and audit AI interactions without requiring developers to write extensive custom code.

Native Integration: The "Zero-Code" Approach The most efficient way to achieve your goal is by enabling the Microsoft Purview integration directly within your Azure subscription or AI Foundry project.

Turn-on-and-go: Azure Admins can enable a single setting at the subscription level.

Automatic Data Flow: Once enabled, prompts and responses from Azure AI-based apps flow into Purview immediately.

Centralized Hub: Use the Microsoft Purview AI Hub to visualize AI activity and detect sensitive data leaks across your entire tenant.

Box 2: Azure Monitor

Monitors performance metrics and operational health for the models

For monitoring Azure OpenAI models with an Azure-native approach and minimal effort, the most adequate solution is Azure Monitor. Specifically, utilizing the Azure OpenAI Insights workbook provides a pre-built, comprehensive dashboard for tracking operational health and performance metrics without custom code.

Azure Monitor (Platform Metrics) Azure Monitor automatically collects "Platform Metrics" for every Azure OpenAI resource at no additional cost or configuration. These provide near real-time visibility into basic operational health:

Total Requests: Track volume and status codes (e.g., 200 Success vs. 429 Rate Limited).

Latency: Monitor "Time to Response" to ensure performance meets user expectations.

Token Consumption: View "Processed Inference Tokens" and "Generated Completion Tokens" to manage costs and quota limits.

QUESTION 32

A company has Microsoft Copilot Studio agents.

The company plans to deploy custom connectors across development, test and production environments. You need to design an application lifecycle management (ALM) process to ensure consistency and prevent direct editing in production.

Which two actions should you include in the design? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

A. Deploy managed solutions to production.

B. Deploy unmanaged solutions to production.

C. Manually rebuild the agents in each environment.

D. Move the agents between the environments by using data export and import.

E. Include agents and connectors in a solution.

---

Correct Answer: AD Section: (none) Explanation/Reference:

Explanation:

Core ALM Actions To ensure consistency and governace, include these actions in your design:

1. Environment & Solution Strategy

[A] *-> Three-Environment Model: Establish a dedicated Development (unmanaged), Test/UAT (managed), and Production (managed) environment.

Solution Packaging: Create agents and custom connectors directly inside a Power Platform Solution.

[D] *-> Managed Solutions: Always export your solution as Managed when moving to Test and Production. This locks the components, preventing direct editing in those environments.

QUESTION 33

A company uses multiple Microsoft Copilot Studio agents across different channels.

You need to recommend a monitoring solution that provides comprehensive telemetry data and performance insights for the agents.

What should you include in the recommendation?

A. Application Insights

B. Microsoft Dynamics 365 Customer Voice

C. Log Analytics

D. Microsoft Purview

---

Correct Answer: A

Explanation/Reference:

Explanation:

Azure Application Insights (part of Azure Monitor) is the best Microsoft solution for monitoring comprehensive telemetry and performance for Copilot Studio agents across multiple channels.

While Copilot Studio has built-in analytics, Application Insights allows you to centralize data from many different agents and channels into one unified view.

Why Use Azure Application Insights?

Connecting your agents to Application Insights provides deeper technical and operational visibility that the standard dashboard lacks:

Centralized Monitoring: View telemetry for all your agents in a single Azure resource rather than checking each agent individually in Copilot Studio.

Custom Kusto Queries: Use KQL (Kusto Query Language) to run complex analyses, such as identifying common errors, measuring specific topic latency, or tracking custom events.

Real-Time Alerts: Set up proactive alerts to notify you if an agent has a high error rate, spike in latency, or fails to respond.

Enhanced Transcripts: Capture detailed message-level logs, including user prompts and agent responses, to troubleshoot specific conversation failures.

QUESTION 34

A company has an AI solution named Solution1 that is deployed to the production environment. Solution1 uses an Azure OpenAI model to generate marketing emails for existing customers.

During an internal review, you identify that Solution1 creates different emails depending on the customers’ traits.

You need to recommend a strategy to mitigate the bias. The strategy must adhere to Microsoft responsible AI principles.

What should you recommend?

A. Modify Solution1 to randomly generate emails for different traits.

B. Modify the system instructions of Solution1.

C. Retrain the model by using a larger dataset.

D. Modify the contents of the training dataset.

---

Correct Answer: B Section: (none)

Explanation/Reference:

Explanation:

To reduce bias in your Azure OpenAI email generation system while adhering to Microsoft’s Responsible AI (RAI) Principles, you should implement a multi-layered approach within your System Instructions.

The goal is to move from generic prompts to specific, constraint-based instructions that enforce Fairness and Inclusiveness.

QUESTION 35

A company has a canvas app named App1 in a Microsoft Power Platform environment named Env1. Env1 uses a customer-managed key for data encryption. App1 connects to multiple data sources to retrieve and update customer and order information.

You need to recommend a solution to add Microsoft Copilot components to App1.

The solution must NOT modify the current security or encryption configurations of Env1.

What should you include in the recommendation?

A. Modify the data sources of App1 to make them compatible with Copilot.

B. Duplicate App1 and republish the app in Env1.

C. Enable Copilot features for Env1.

D. Move App1 to a new environment that uses Microsoft-managed keys.

---

Correct Answer: D Section: (none)

Explanation/Reference:

Explanation:

To add Microsoft Copilot components to your canvas app without changing the current environment's security or encryption (Customer-Managed Key), you should move the app to a new environment that uses Microsoft-managed keys.

Core Technical Limitation Microsoft Power Platform environments configured with a Customer-Managed Key (CMK) currently do not support certain Copilot and generative AI features. These features continue to rely on Microsoft-managed encryption keys for their specific internal data processing.

QUESTION 37

After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.

A company has a team that analyzes its customers by using a manual process.

You are designing an AI-based agent to automate and improve the process.

You need to recommend on which platform to build the agent. The solution must meet the following requirements:

Use generative AI to answer common questions. Provide analytics to review AI performance. Identify customer demographics.

Minimize custom development.

Solution: You recommend Microsoft Security Copilot.

Does this meet the goal?

A. Yes

B. No

Correct Answer: B Section: (none)

Explanation/Reference:

Explanation:

Correct:

• You recommend Microsoft Copilot Studio.

Copilot Studio is specifically designed to create customizable AI agents that automate business workflows with minimal coding.

Generative AI Answers: It uses "Generative Answers" to scan your specific data (websites, files, or SharePoint) to answer customer-related questions instantly.

Analytics Dashboard: It includes built-in analytics to track resolution rates, customer satisfaction (CSAT), and overall AI performance.

Customer Demographics: You can configure the agent to extract specific entities (like age, location, or industry) from conversations to build demographic profiles.'

Low-Code/No-Code: It minimizes custom development by providing a visual interface to build logic, rather than writing raw code.

Incorrect:

• You recommend GitHub Copilot.

• You recommend Microsoft Security Copilot.

Low-Code/No-Code: It minimizes custom development by providing a visual interface to build logic, rather than writing raw code.

Incorrect:

• You recommend GitHub Copilot.

• You recommend Microsoft Security Copilot.

QUESTION 38

After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.

A company has a team that analyzes its customers by using a manual process.

You are designing an AI-based agent to automate and improve the process.

You need to recommend on which platform to build the agent. The solution must meet the following requirements:

Use generative AI to answer common questions. Provide analytics to review AI performance. Identify customer demographics.

Minimize custom development.

Solution: You recommend Microsoft Copilot Studio.

Does this meet the goal?

A. Yes

B. No

---

Correct Answer: A Section: (none)

Explanation/Reference:

Explanation:

Correct:

• You recommend Microsoft Copilot Studio.

Copilot Studio is specifically designed to create customizable AI agents that automate business workflows with minimal coding.

Generative AI Answers: It uses "Generative Answers" to scan your specific data (websites, files, or SharePoint) to answer customer-related questions instantly.

Analytics Dashboard: It includes built-in analytics to track resolution rates, customer satisfaction (CSAT), and overall AI performance.

Customer Demographics: You can configure the agent to extract specific entities (like age, location, or industry) from conversations to build demographic profiles.' Low-Code/No-Code: It minimizes custom development by providing a visual interface to build logic, rather than writing raw code.

Incorrect:

• You recommend GitHub Copilot.

• You recommend Microsoft Security Copilot.

QUESTION 39

A company uses multiple Microsoft Copilot Studio agents across different channels.

You need to recommend a monitoring solution that provides comprehensive telemetry data and performance insights for the agents.

What should you include in the recommendation?

A. Microsoft Power BI

B. the Analytics tab in Copilot Studio

C. Log Analytics

D. Azure Advisor

Correct Answer: A Section: (none)

Explanation/Reference:

Explanation:

Correct:

• Application Insights To achieve comprehensive monitoring, telemetry, and performance insights for Microsoft Copilot Studio agents across different channels, you should integrate them with Azure Application Insights.

Integrating Application Insights provides a centralized view of agent health, user interactions, topic performance, and latency, which is crucial for monitoring multi-channel deployments.

• Microsoft Power BI is the best tool for monitoring comprehensive telemetry data and performance insights across multiple Copilot Studio agents and various channels.

Analytics tab within Copilot Studio offers quick, high-level insights for individual agents, Power BI provides the necessary scalability for enterprise-level, multi-agent monitoring.

Centralized Multi-Agent View: Power BI allows you to create custom dashboards that aggregate data from multiple agents and environments (e.g., using the Power-CAT Agent Insights Hub).

Deep Telemetry Integration: Power BI can ingest detailed session data and chat transcripts, enabling deep analysis of topic triggers, tool execution, and user satisfaction (CSAT) across channels.

Customization and Reporting: You can leverage Power BI templates, such as the Copilot Studio agent report, to analyze trends over long periods, which the built-in analytics tab does not support.Enhanced Monitoring with Application Insights: By connecting agents to Azure

*-> Application Insights, you can export detailed telemetry to Power BI for comprehensive, long-term monitoring, including conversation transcripts and custom events.

Incorrect:

• Azure Advisor * Azure DevOps * Log Analytics * Microsoft Dynamics 365 Customer Voice * Microsoft Purview * the Analytics tab in Copilot Studio The built-in Analytics tab within Copilot Studio offers quick, high-level insights for individual agents only.