AB-620 exam dumps

Microsoft AB-620 Value Package

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  • Exam Code: AB-620
  • Exam Name: Designing and Building Integrated AI Agent Solutions in Copilot Studio
  • No. of Questions: 101 Questions and Answers
  • Updated: Jul 28, 2026

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  • Total Questions: 101
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Microsoft AB-620 Exam Syllabus Topics:

SectionObjectives
Integrate External Systems and Data Sources- Integrating Dataverse and Power Platform components
- Connecting Azure services and APIs
- Using Power Automate for workflow orchestration
Build and Configure AI Agents in Copilot Studio- Creating and configuring copilots and topics
- Configuring actions, plugins, and connectors
- Using generative AI and prompt engineering in Copilot Studio
Deploy, Monitor, and Optimize AI Agents- Iterative improvement and lifecycle management
- Publishing and deploying copilots
- Monitoring performance and analytics
Governance, Security, and Compliance- Managing access control and authentication
- Data protection and responsible AI practices
- Environment management in Power Platform
Plan and Design Copilot Studio AI Agents- Selecting Copilot Studio capabilities and architecture approach
- Designing conversation flows and agent behavior
- Requirements analysis for AI agent solutions

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

1. A company uses an agent in Copilot Studio to generate structured responses for internal users.
The agent must meet the following requirements:
- Consistently follow a reusable instruction template for response tone and structure.
- Use an enterprise-approved foundation model for responses generated
through the template.
You need to configure custom prompts so the agent uses the Microsoft Foundry model catalog.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Publish the agent to apply the Foundry model selection automatically.
B) Create a custom prompt template and apply it where the agent generates the structured response.
C) Enable citations, so the model is restricted to approved outputs.
D) Configure Azure AI Search as the grounding source, so the model choice is enforced.
E) Allow topic authors to define tone and structure directly in topic steps.
F) Select a model from the Foundry model catalog for the custom prompt configuration.


2. Hotspot Question
A company uses an agent that invokes an agent flow to exchange information during a conversation.
The company requires that the agent send data into the flow and receive structured results back from the same flow run. To support this business need, the flow must be configured to do the following:
- Capture the data provided by the agent.
- Return data results to the agent.
You need to configure the flow so that it can exchange data with the agent.
What should you configure for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


3. 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 determine an appropriate implementation related to the use of agent flows that is based on Blue Vender's design and compliance standards.
Which implementation method should you use for each scenario? To answer, move the appropriate implementation methods to the correct scenarios. 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.


4. An agent needs to call an external REST API that isn't available as a pre-built connector, and the API requires OAuth 2.0 authentication. What should you create?

A) A new environment variable only
B) A custom connector with an OAuth 2.0 authentication type
C) A generative answers node
D) A Power Automate flow with anonymous authentication


5. An agent needs to call an external REST API that isn't available as a pre-built connector, and the API requires OAuth 2.0 authentication. What should you create?

A) A new environment variable only
B) A custom connector with an OAuth 2.0 authentication type
C) A generative answers node
D) A Power Automate flow with anonymous authentication


Solutions:

Question # 1
Answer: B,F
Question # 2
Answer: Only visible for members
Question # 3
Answer: Only visible for members
Question # 4
Answer: B
Question # 5
Answer: B


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