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| Certification Vendor: | Microsoft |
| Exam Name: | Designing and Building Integrated AI Agent Solutions in Copilot Studio |
| Exam Number: | AB-620 |
| Exam Format: | Multiple choice, Multiple select, Case studies, Scenario-based questions |
| Available Languages: | English |
| Exam Duration: | 100-120 |
| Related Certifications: | Microsoft Certified: Power Platform Functional Consultant Associate Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Power Platform Developer Associate |
| Passing Score: | 700/1000 |
| Certificate Validity Period: | 1 year (typical Microsoft certification renewal cycle) |
| Real Exam Qty: | 40-60 |
| Exam Price: | USD 165 (varies by region) |
| Recommended Training: | Microsoft Learn - Build AI agents with Copilot Studio Power Platform and Copilot Studio training modules |
| Exam Registration: | Microsoft Learn - Copilot Studio Learning Paths Microsoft Credentials - Certification Overview |
| Sample Questions: | Microsoft AB-620 Sample Questions |
| Exam Way: | Online proctored (Pearson VUE or Microsoft-proctored online exam depending on region) |
| Pre Condition: | No formal prerequisites required. Recommended: basic understanding of Microsoft Power Platform, Azure AI services, and conversational AI concepts. |
| Official Syllabus URL: | https://learn.microsoft.com/credentials/certifications/ |
| Section | Objectives |
|---|---|
| Topic 1: Governance, Security, and Compliance | - Data protection and responsible AI practices - Environment management in Power Platform - Managing access control and authentication |
| Topic 2: Deploy, Monitor, and Optimize AI Agents | - Monitoring performance and analytics - Iterative improvement and lifecycle management - Publishing and deploying copilots |
| Topic 3: Plan and Design Copilot Studio AI Agents | - Designing conversation flows and agent behavior - Requirements analysis for AI agent solutions - Selecting Copilot Studio capabilities and architecture approach |
| Topic 4: Integrate External Systems and Data Sources | - Integrating Dataverse and Power Platform components - Using Power Automate for workflow orchestration - Connecting Azure services and APIs |
| Topic 5: Build and Configure AI Agents in Copilot Studio | - Configuring actions, plugins, and connectors - Using generative AI and prompt engineering in Copilot Studio - Creating and configuring copilots and topics |
1. A team is standardizing ALM for agents in Copilot Studio.
The team requires a custom solution that includes agents. The solution must support ALM scenarios, such as managing and transporting agent assets across environments and pipeline deployments.
You need to create an ALM-ready custom solution in Copilot Studio.
What should you do?
A) Export the custom solution as a managed solution and import it into production.
B) Export the agent directly and then import it into another environment.
C) Publish the agent to a channel and use that channel configuration as the ALM container.
D) Create a new custom solution from the Solutions area.
2. 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 evaluate whether the current configuration decisions for the Blue Yonder Copilot agent comply with the company's security and governance policies.
Which compliance status should you assign to each configuration decision? To answer, move the appropriate compliance statuses to the correct configuration decisions. You may use each compliance status 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. You need an agent built in Copilot Studio to invoke tools hosted on an external server using a standardized protocol that exposes tool schemas and capabilities for consumption by AI models.
Which protocol should you use?
A) SAML
B) SOAP
C) SMTP
D) Model Context Protocol (MCP)
4. An agent needs to display a rich, interactive form (with dropdowns and buttons) to collect structured input from the user in Microsoft Teams. What should you use?
A) A trigger phrase
B) Adaptive card
C) A generative answers node
D) Plain text message node
5. A regulated company requires that all agent conversations be logged, and that administrators can review transcripts for compliance auditing. Which two features should you configure? (Choose two.)
A) Turn off the Data Loss Prevention (DLP) policy
B) Enable Copilot Studio analytics and conversation transcript retention
C) Disable conversation transcripts
D) Application Insights / analytics integration
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: Only visible for members | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: B,D |
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