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| Section | Weight | Objectives |
|---|---|---|
| Build and extend agents in Copilot Studio | 40–45% | - Implement advanced capabilities
|
| Test, deploy, and manage agents | 20–25% | - Test and validate agent performance
|
| Plan and configure agent solutions | 30–35% | - Plan an agent solution
|
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NEW QUESTION # 116
A company needs an agent in Copilot Studio to complete tasks by interacting with a legacy desktop application that does not use APIs. The builder needs that UI automation can run in the supported execution context and needs a way to inspect how the automation behaves during testing conversations. to validate To meet the business needs, the solution must meet the following requirements:
* Enable the agent to perform UI automation against the legacy application.
* Inspect execution details for the automation during conversations.
You need to configure the agent based on the requirements.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Computer use is the Copilot Studio capability for operating a website or desktop application ' s graphical interface when an API is unavailable. Enabling it gives the agent a UI automation tool driven through the supported machine execution context. During testing, the builder can open the computer-use activity or remote session from the agent ' s activity view to observe steps, inspect logs, and understand failures in real time. Adding a desktop flow is a different deterministic automation technology and is not required by the stated computer-use design.
Publishing alone does not provision the UI automation or its machine. A custom connector cannot automate screen controls when the application exposes no API. The tool should be configured with narrowly scoped instructions, a healthy supported machine, protected credentials, and human confirmation for sensitive actions. Because computer-use behavior is probabilistic and visual interfaces change, the team should test alternate screen states, pop-ups, timing, and recovery, then monitor production sessions under strict access and retention controls. Study Guide alignment: Integrate and extend agents in Copilot Studio > Add tools to agents > Configure and monitor computer use for an agent.
NEW QUESTION # 117
Hotspot Question
You run multiple evaluation tests for an agent in Copilot Studio before expanding user access.
The tests provide the following results:
- Each evaluation case is reported as meeting or missing the expected
response.
- Some evaluation cases fail repeatedly across several runs.
- Each run displays the expected response and the response generated by the agent.
You need to provide a conclusion based on the evaluation results.
Which conclusions should you make? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Pass or fail status
Based on the testing criteria in Microsoft Copilot Studio, the outcome described directly measures the Pass or fail status of your tests.
Pass or fail status: This is the primary conclusion. Microsoft Copilot Studio Agent Evaluation uses structured methods (such as Exact Match, Similarity, or Compare Meaning) to objectively check if your agent met or missed the expected responses in your test set.
Box 2: Consistent outcomes
The conclusion to make from this is Consistent outcomes.
When evaluation test cases fail repeatedly across several runs, it indicates a stable, reproducible issue with the agent's behavior rather than random variability. Because the agent produces the same failure under the same test conditions, you have consistent outcomes.
Box 3: Expected and generated response
From the multiple evaluation tests in Microsoft Copilot Studio, the primary conclusion you can make is regarding the expected and generated responses.
This specific test output allows you to directly assess the alignment between what the AI was anticipated to say (the expected response) and what it actually produced (the generated response). By contrasting these, you can analyze semantic similarity, intent, and overall quality.
Reference:
https://www.microsoft.com/en-us/microsoft-copilot/blog/copilot-studio/how-to-evaluate-ai-agents/
NEW QUESTION # 118
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 deploy the Blue Yonder Copilot agent to the public website and Microsoft Teams while ensuring compliance with the company's security and Responsible AI requirements.
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: B,D
Explanation:
[A]
You can configure prompt modifications at the system and agent level in Microsoft Copilot Studio to satisfy your organization's Responsible AI (RAI) guidelines.
[E]
Scenario:
Compliance and security
Responsible AI content moderation filters must be enabled.
Reference:
https://microsoft.github.io/agent-academy/operative/06-ai-safety/
NEW QUESTION # 119
You need to design a solution that provides Fabrikam Inc. with a multi-agent design approach with existing agents.
Which approach should you use for each requirement? To answer, move the appropriate approaches to the correct requirements. You may use each approach 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.
Answer:
Explanation:
NEW QUESTION # 120
You need to implement tool usage in topics that meet the Blue Yonder design and governance requirements.
Which implementation method should you use for each requirement? To answer, move the appropriate implementation methods to the correct requirements. You may use each implementation method once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 121
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