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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Integrate and Extend Agents in Copilot Studio | 40-45% | - Integrate agents with enterprise systems
|
| Topic 2: Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
| Topic 3: Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
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NEW QUESTION # 126
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.
Answer: B,D
Explanation:
[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/
NEW QUESTION # 127
A team is preparing to manage agents in Copilot Studio by using ALM from Power Platform.
A solution must be created before agents and configuration of assets can be managed through ALM.
You need to create a solution that can contain agents and related assets.
Which three actions should you perform in order? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
1. Open the Solutions area in Copilot Studio; 2. Define the solution name and publisher; 3. Save the solution container.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Solution creation begins in the Solutions area because that is the Copilot Studio entry point to the Power Platform solution explorer. The maker then supplies the solution name and publisher. The publisher is not cosmetic: it determines the customization prefix and forms part of the ownership and naming strategy for components that will move through ALM. Saving creates the solution container, after which agents, flows, connection references, environment-variable definitions, prompts, and other dependent assets can be added. Reviewing the solution details page can follow creation but is not one of the required creation steps in this three-action sequence. A custom solution is preferable to relying on the default solution for controlled export, source management, and pipeline deployment. Before export, the team should use dependency checks to ensure all assets required by the agent are included and should avoid including unrelated components. Downstream releases normally import a managed build of the solution, while development remains unmanaged so authorized makers can continue editing. Study Guide alignment: Test and manage agents > Implement application lifecycle management for agents in Copilot Studio > Create a solution.
NEW QUESTION # 128
Which two actions should you perform before making the agent available on both channels? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
A . Configure prompt modifications at the system level. Centralized instructions enforce the required tone, disclaimers, response boundaries, and refusal behavior consistently across generative responses. Microsoft documents that prompt modification can define an agent's personality, response format, permitted subjects, and behavior when an answer is unavailable. This avoids inconsistent manual changes across individual topics. Microsoft: Prompt modification D . Configure Power Platform DLP policies. DLP policies govern which connectors, knowledge sources, HTTP endpoints, and channels the agent may use. They should be configured and validated before publication because a policy violation can prevent the agent from being published. DLP also protects against unauthorized data movement between business and non-business connectors. Microsoft: Data policies for agents Why the others are incorrect: B creates duplicated, inconsistent disclaimers. C incorrectly treats moderation as a web-channel setting; moderation is configured for generative behavior rather than enforced only by embedding settings. E applies safeguards after publication and assumes filters must be configured separately for every channel, which would not provide the required centralized governance.
NEW QUESTION # 129
An agent calls a flow. The agent requires structured output values to be returned.
The agent receives unexpected or empty values.
You need to configure the agent so that data is exchanged correctly between the agent and the flow.
What should you do?
Answer: E
Explanation:
Validating your parameter definitions is the correct first step. Unexpected or empty values typically occur because of a schema mismatch or because unsupported, nested data types are passed directly between the agent and the Power Automate flow.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/advanced-flow-create
NEW QUESTION # 130
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.
Answer: C,D
Explanation:
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/
NEW QUESTION # 131
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