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| Section | Weight | Objectives |
|---|---|---|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Build advanced agent solutions
|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
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질문 # 66
Case Study 1 - Blue Yonder Airlines
Background
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and international flights. The company serves millions of passengers annually through its website, mobile app, and call centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels - web chat, mobile app, and Microsoft Teams (for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human agents when needed.
The project is led by a cross-function team:
- Product manager: Defines requirements and success metrics.
- Lead agent author: Designs topics, intents, and generative behavior.
- Flow designers: Build agent flows and integrations.
- IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment
Channels
Public website: Embedded web chat
Mobile app: In-app chatbot
Microsoft Teams: Internal support agent access
Identity and access
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements
Omnichannel support
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must also support internal staff.
Self-service capabilities
The agent must handle common inquiries such as:
- Flight status
- Booking and rebooking
- Loyalty program questions
- Travel policies and baggage rules
Human escalation
If the agent cannot resolve an issue or the user requests help, it must:
- Escalate to a human agent.
- Transfer the conversation transcript and relevant context.
- Redact any sensitive personal data before escalation.
Knowledge integration
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A topics for each document.
Performance metrics
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs
CSAT: ≥85% for AI-handled interactions
Technical requirements
Platform constraints
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must be avoided.
Monitoring and maintenance
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Topics, flows, and knowledge sources must be updated as policies or systems evolve.
Issues and constraints
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents.
Large files must be split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations.
Prompt modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across channels.
Problem statement
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio. The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise systems, and support both anonymous and authenticated users. It must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
You need to ensure that every AI-generated response from the agent in Copilot Studio includes a disclaimer that complies with the company's security and governance policies.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
정답：B,C
설명：
[B]
Using prompt modification in the Generative Answers node settings is an excellent and highly effective strategy for embedding compliance disclaimers into your agent's responses.
[A]
Adding a mandatory disclaimer to your greeting message is the best practice for agent governance. You can enforce this by configuring your Greeting System Topic and adding formal
"Output Rules" to the agent's core instructions.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-boost-node
https://www.reddit.com/r/copilotstudio/comments/1pje5fy/how_do_you_handle_ai_disclaimers_in
_copilot/
질문 # 67
Drag and Drop Question
A company builds agents in Copilot Studio in a development environment.
The agents are packaged inside a solution and deployed by using Power Platform Pipelines to test and production environments.
The company has the following requirements that must be met:
- Production deployments are limited to a defined set of users who are
responsible for that stage.
- The same solution is reused across all environments without editing
its components.
- The production environment always receives a locked-down version of
the solution.
You need to configure the pipeline and solution behavior to meet the requirements.
What should you configure? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
Box 1: Configure stage access for the production stage
To meet this specific requirement, you should configure stage access for the production stage.
Box 2: Use environment variables in the solution.
To deploy the exact same solution across all environments without modifying its components, you must use environment variables in the solution. This allows you to externalize environment- specific configurations (like connection references and URLs) so they adapt to each target environment without altering the core package.
Box 3: Deploy the solution as managed
To meet the requirement of ensuring that the production environment always receives a locked- down version of the solution, you must In Microsoft Power Platform, deploying a solution as managed locks down the components in the target environment. Users cannot make direct edits or modifications to the agents or other components in that production environment, ensuring stability, security, and strict application lifecycle management (ALM).
Reference:
https://microsoft.github.io/mcs-labs/labs/mcs-alm/
질문 # 68
You need to connect Operations Concierge to Fabrikam Inc. ' s Azure AI Search knowledge index while complying with security requirements.
Which configuration should you use for each requirement? To answer, move the appropriate configurations to the correct requirements You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point
정답：
설명：
Explanation:
Authenticated governed access # Select service-principal authentication; Required curated vector index
# Enter the Azure AI Search index name; Correct Azure AI Search service instance # Provide the Azure AI Search endpoint URL.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: An Azure AI Search connection needs three distinct pieces of configuration. The endpoint identifies the search-service instance that hosts Fabrikam ' s indexed documents. The index name then selects the specific vector index containing the curated policies and procedures. Authentication determines how Copilot Studio is authorized to query that service. Because the scenario requires governed application access rather than a maker ' s personal identity, the service-principal option is the appropriate selection from the choices provided. Enabling citations is useful after retrieval is configured, but it does not establish the service connection or select an index. Microsoft recommends creating Azure AI Search through the supported data-source connection experience rather than manually assembling an unsupported endpoint/key combination. Administrators should grant the service principal only the permissions needed for query operations, protect its credentials, and maintain separate configuration per environment. Testing should confirm that the intended index-not another index in the same service-is queried, that unauthorized content is excluded, and that policy responses cite material that actually supports the generated guidance. Study Guide alignment: Integrate and extend agents in Copilot Studio > Connect to enterprise knowledge sources > Connect to Azure AI Search.
질문 # 69
An agent's generative answers responses sometimes include information not present in any configured knowledge source. What should you do to reduce this behavior?
정답：C
설명：
Restricting the generative answers node (or agent instructions) to only use configured knowledge sources reduces hallucinated content that isn't grounded in approved data.
질문 # 70
A company uses an agent flow that calls a connector action. The flow sends an administrative notification if the action fails or times out.
Administrators require the following configuration to help troubleshoot and manage failures:
- Handle failure and timeout outcomes explicitly.
- Continue execution after a failure is handled.
- Avoid retrying the failed action automatically.
You need to configure the agent flow so that failures are handled in a controlled and predictable way.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
정답：A,C
설명：
To handle failures and timeouts explicitly without automatic retries while ensuring the flow continues, take these two configuration steps in the Power Automate designer:
[D] Configure Run After settings on the notification/recovery step to trigger on "has failed" and
"has timed out" status options from the primary connector action.
[B] Scope Actions: Grouping your connector action and its immediate steps inside a Scope action allows you to centrally manage errors. You can set the subsequent administrative notification to run only if the entire Scope fails or times out. This satisfies the requirement to handle failure and timeout outcomes explicitly in a clean, predictable way Reference:
https://d365demystified.com/2022/01/20/try-catch-error-handling-using-scope-in-power-automate/
질문 # 71
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