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Microsoft AB-620 Exam Syllabus Topics:

Microsoft Designing and Building Integrated AI Agent Solutions in Copilot Studio Sample Questions:

1. Drag and Drop Question
You run the same fixed test set three times in Copilot Studio.
During evaluation, you observe the following:
- The same interaction fails in all three runs.
- Score values range from 0.58 to 0.61.
- The reasoning states that the response partially matches the expected answer.
- The knowledge source that is used is internal documentation.
- No tools are invoked.
You need to determine which conclusions are supported based on the evaluation results.
Which conclusions should you make? To answer, move the appropriate conclusions to the correct evaluation results. You may use each conclusion 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.

2. Drag and Drop Question
A company is extending agents in Copilot Studio with both external capabilities and enterprise content access. Some user requests require grounded answers, while other requests require executing actions.
To meet the business needs, the agent must meet the following requirements:
- Ground answers using results from enterprise data.
- Invoke callable functions exposed through a standardized tool
interface.
- Write an update to a system by using an authenticated action during
the conversation.
You need to integrate the correct approach to meet the requirements.
What should you integrate for each requirement? To answer, move the appropriate integrations to the correct requirements. You may use each integration 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.

3. An agent must escalate to a live human agent when it cannot resolve a customer issue, and hand off full conversation context. Which node should you add to the topic?

A) Adaptive card node
B) Escalate to a live agent (handoff) node
C) Redirect to another topic node
D) End of conversation node

4. 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.
Drag and Drop Question
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. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

5. An agent in Copilot Studio must retrieve real-time data from an external system that exposes a REST API.
The API returns structured JSON data and requires authentication.
The agent must call the API during conversations to fulfill user requests.
The agent must retrieve real-time data from the external system by calling an authenticated REST API during a conversation.
The solution must use a supported mechanism that executes the REST API call and the call must be explicitly configured to run at runtime.
You need to determine which approaches add the REST API to the agent.
Which two solutions meet the goal? Each correct answer is a complete solution.
NOTE: Each correct selection is worth one point.

A) Configure an HTTP action and invoke it from a topic during the conversation.
B) Add the REST API as a knowledge source so the agent can query it during conversations.
C) Create a global variable to store the API URL and call it using a Redirect node.
D) Enable generative answers and rely on the model to fetch the REST API data automatically.
E) Add the REST API as a tool and call it either by using a topic or agent instruction.
F) Create a topic variable and use a Formula to parse the API endpoint string.

Solutions: