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| Section | Objectives |
|---|---|
| Topic 1: Deploy, Monitor, and Optimize AI Agents | - Monitoring performance and analytics - Iterative improvement and lifecycle management - Publishing and deploying copilots |
| Topic 2: Plan and Design Copilot Studio AI Agents | - Requirements analysis for AI agent solutions - Designing conversation flows and agent behavior - Selecting Copilot Studio capabilities and architecture approach |
| Topic 3: Build and Configure AI Agents in Copilot Studio | - Using generative AI and prompt engineering in Copilot Studio - Configuring actions, plugins, and connectors - Creating and configuring copilots and topics |
| Topic 4: Governance, Security, and Compliance | - Data protection and responsible AI practices - Managing access control and authentication - Environment management in Power Platform |
| Topic 5: Integrate External Systems and Data Sources | - Using Power Automate for workflow orchestration - Integrating Dataverse and Power Platform components - Connecting Azure services and APIs |
For the recognition of skills and knowledge, more career opportunities, professional development, and higher salary potential, the Microsoft AB-620 certification exam is the proven way to achieve these tasks quickly. Overall, we can say that with the Designing and Building Integrated AI Agent Solutions in Copilot Studio (AB-620) exam you can gain a competitive edge in your job search and advance your career in the tech industry.
NEW QUESTION # 103
A company is designing an agent flow that includes human in the loop stages during execution.
The company requires that the agent flow perform the following actions:
Must wait for a human decision before it resumes.
Must collect information and then continue execution.
You need to configure the flow behavior.
Answer:
Explanation:
NEW QUESTION # 104
Drag and Drop Question
A company uses a supported Power Platform connector to provide real-time access to enterprise records for knowledge grounding in an agent in Copilot Studio.
To meet the business needs, the knowledge source must provide the following functionality:
- Avoid copying enterprise data into an index.
- Keep source-system access controls enforced.
- Access data by calling the system at runtime.
You need to configure the connector knowledge source.
What should you configure for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration 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:
Explanation:
Box 1: Use a real-time connector
Use a real-time connector to meet this requirement.
Power Platform connectors configured as real-time knowledge sources execute queries live at runtime under the user's connection and identity. Because the data is retrieved on demand directly from the source system, no data movement or replication takes place, completely avoiding copying enterprise data into a Microsoft 365 or Graph index.
Box 2: Use existing permissions
To meet the requirement of keeping source-system access controls enforced while using a supported Power Platform connector for real-time knowledge grounding in Microsoft Copilot Studio, you should use existing permissions.
Delegated Context: When structured Power Platform connectors are integrated as real-time knowledge sources, they execute queries dynamically in the security context of the user interacting with the agent.
Access Enforcement: By relying on use existing permissions, the underlying data source maps the authenticated user's credentials (such as Microsoft Entra ID) to ensure they only retrieve and see records they are explicitly authorized to view.
Computer Information Agency
Box 3: Retrieve data without indexing
To meet the requirement of accessing real-time data by calling the system at runtime using a Power Platform connector, you should retrieve data without indexing.
When you use a Power Platform connector for knowledge grounding in Copilot Studio, it functions via dynamic runtime queries:
No Pre-indexing Required: Unlike static knowledge sources, connectors fetch live records directly from the source system at the exact moment the user asks a question.
Real-Time Accuracy: Avoiding an external search index ensures that the AI agent always accesses the most current, up-to-the-minute enterprise data.
Reference:
https://suparnatechbasket.wordpress.com/2025/09/15/copilotstudio-realtime-connector-vs-graphconnector/
NEW QUESTION # 105
A company is configuring an agent flow that uses multiple action types to perform operations and process data.
The flow must be configured as follows:
An HTTP action must connect to an external service.
A data action must reference the correct data to process.
You need to configure the settings for each action type.
Answer:
Explanation:
Explanation:
HTTP action # Endpoint and authentication; Data action # Table relationships and keys.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: An HTTP action must know where to send the request and how the destination authenticates it. The endpoint, method, headers, and authentication or connection details therefore belong to the HTTP action ' s configuration. A data action operates against structured records, so table relationships and key fields determine which entity and row are read or changed and how related data is resolved. Input mapping is important for both action types but does not replace these defining settings. Timeout and retry policy control resilience after an action has been configured; they do not identify the endpoint or the record relationship. The flow designer should also validate schemas, map outputs into clearly typed variables, and provide failure paths for authorization, not- found, timeout, and malformed-response conditions. Keys should be stable identifiers rather than display names, and connection permissions should follow least privilege. Testing with both valid and invalid records confirms that the data action targets the intended row and that the HTTP action cannot silently call an incorrect or unauthenticated endpoint. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Configure actions and connectors.
NEW QUESTION # 106
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,E
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 # 107
Drag and Drop Question
A team is preparing to assess an agent in Copilot Studio before expanding access to additional users.
The team requires an evaluation that provides controlled, repeatable, and consistently measured test runs.
The evaluation must:
- Be triggered directly by the team to control when testing occurs.
- Determine success based on clearly established acceptance criteria.
- Rely on a predefined source that ensures consistency across repeated
runs.
You need to configure the evaluation to meet the requirements.
What should you configure? To answer, move the appropriate configurations to the correct evaluation requirements. You may use each configuration 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:
Explanation:
Box 1: Execute the evaluation on demand
To trigger structured, repeatable agent evaluations manually inside Microsoft Copilot Studio so your team can precisely control when testing occurs, you should click Evaluate directly from the Evaluate tab within the Copilot Studio user interface.
Selecting this option initiates an on-demand, interactive test run against your defined test sets.
Box 2: Comparing generated responses against defined expectation
Comparing generated responses against defined expectations is exactly how you establish pass/fail signals. Microsoft Copilot Studio automates this process so you can achieve controlled, repeatable, and consistently measured tests before expanding access.
Box 3: Use a curated prompt list as the interaction source.
Using a curated prompt list-known as an evaluation test set-is exactly how you ensure consistency. It removes subjective, one-off testing and establishes a structured framework for measuring response quality.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/analytics-agent-evaluation-overview
NEW QUESTION # 108
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