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| Section | Weight | Objectives |
|---|---|---|
| Deploy AI-powered business solutions | 40–45% | - Design ALM processes
|
| Plan AI-powered business solutions | 25–30% | - Analyze requirements for AI-powered business solutions
|
| Design AI-powered business solutions | 25–30% | - Orchestrate configuration
|
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NEW QUESTION # 19
What should you recommend to assist the CEO with their specific responsibilities?
Answer: B
Explanation:
The CEO's responsibility is to ensure that all AI solutions adhere to industry-standard responsible AI practices . The case study also explicitly says the CEO wants a quarterly assessment that must verify:
* reliability
* interpretability
* fairness
* compliance
The best recommendation is D. the Responsible AI dashboard .
Why this is correct:
The Responsible AI dashboard is the Microsoft-recommended capability for evaluating AI systems against responsible AI dimensions such as fairness, interpretability, error analysis, and model behavior assessment. It aligns directly with the CEO's governance-focused responsibility.
Why the other options are not the best fit:
* A. Compliance Center focuses more broadly on Microsoft 365 compliance and governance, not full responsible AI evaluation dimensions like fairness and interpretability.
* B. Microsoft Foundry Tools is too broad and not the specific assessment tool for responsible AI measurement.
* C. the Microsoft Service Trust Portal provides compliance documentation and trust information, but it does not assess Contoso's AI solutions for fairness and interpretability.
* E. Microsoft Purview is strong for data governance, classification, compliance, and auditing, but it is not the dedicated Microsoft tool for responsible AI evaluation across those four dimensions.
NEW QUESTION # 20
Case Study 2 - Contoso, Ltd
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.
What should you recommend to assist the CTO with the prebuilt agent selection process?
Answer: D
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.
Reference:
https://learn.microsoft.com/en-us/dynamics365/copilot/ai-get-started
NEW QUESTION # 21
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?
Answer: C
Explanation:
The requirements are classic Power Platform ALM requirements:
the custom connector must be deployed consistently across environments
it should be editable only in development
The correct design choice is to add the custom connector to Solution1.
Why B is correct:
Putting the custom connector inside the solution makes it part of the ALM package It can then be exported and imported consistently across environments In production, when deployed properly through managed solutions, it is not freely edited there, which supports the requirement that editing happens only in development Why the other options are not correct:
A). Share the custom connector controls access, not ALM packaging and deployment consistency C). Create the custom connector in the default solution is not the recommended ALM approach for controlled deployment D). Add the custom connector to GitHub may help source control, but by itself it does not satisfy Power Platform deployment packaging across environments
NEW QUESTION # 22
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?
Answer: C
Explanation:
The problem is not just that the agent is slow. The telemetry specifically says it frequently reaches its token usage limit. That means too much content is being pulled into the prompt or context window before the model generates the answer.
The best recommendation is D. Reconfigure the prompts to limit the amount of retrieved content from the knowledge sources.
Why D is correct:
It directly targets the root cause: too many tokens from retrieved context It reduces unnecessary context while still keeping the most relevant information It helps preserve response quality better than simply cutting capabilities or hard-limiting output size
NEW QUESTION # 23
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.
Answer:
Explanation:
Explanation:
Test scenario # Run task-based scenarios that involve both apps; Metric # Track the successful completion of cross-app tasks Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answer is D :
* Test scenario # Run task-based scenarios that involve both apps
* Metric # Track the successful completion of cross-app tasks
Why this test scenario is correct
The question explicitly asks for an end-to-end testing design for a Copilot Studio agent that integrates with both:
* Dynamics 365 Customer Service
* Dynamics 365 Sales
The required capabilities are:
* coordinating tasks and data interactions across both apps
* interpreting user input and returning contextually relevant outputs
That means the testing approach cannot be isolated to one app at a time. It must validate the agent's behavior across the full multi-application business workflow.
That is why the correct test scenario is:
Run task-based scenarios that involve both apps
This kind of test validates whether the agent can successfully move through realistic business processes such as:
* reading customer context from one app
* updating or retrieving related sales information in the other
* maintaining context through the workflow
* responding appropriately based on user intent across systems
From an agentic AI business solutions perspective, this is the right design because true enterprise agent validation must focus on workflow execution , not just component-level checks.
Why this metric is correct
The best metric is:
Track the successful completion of cross-app tasks
This is the most direct way to measure whether the agent is actually achieving the intended business outcome across both Dynamics 365 applications.
Why this matters:
* The requirement is about coordination across apps
* The test is end-to-end
* The goal is not just speed or UI consistency
* The agent must complete business tasks successfully across systems
A cross-app completion metric shows whether the agent can:
* understand the user's request
* maintain context
* retrieve or update the right information
* finish the workflow correctly across app boundaries
This is much more meaningful than measuring clicks or simple response time.
Why the other options are incorrect
A). In each app, test isolated tasks without using workflows / Measure initial prompt response time This fails the end-to-end requirement. Isolated tasks do not validate cross-app orchestration, and response time does not prove successful workflow execution.
B). Run task-based scenarios that involve both apps / Track average click rate across both apps The scenario part is good, but average click rate is not the right success metric for Copilot task orchestration.
Clicks do not reliably measure whether the business process was completed correctly.
C). Test visual consistency across both apps / Track successful completion of cross-app tasks The metric is good, but the test scenario is wrong. Visual consistency is a UI concern, not an end-to-end functional validation of cross-app agent behavior.
Expert reasoning
For exam questions like this:
* If the requirement says end-to-end across multiple apps , choose task-based scenarios involving both apps
* If the goal is business workflow success, choose a metric tied to task completion , not visual design, click rate, or raw response speed
NEW QUESTION # 24
......
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