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| Section | Objectives |
|---|---|
| Integrate External Systems and Data Sources | - Using Power Automate for workflow orchestration - Integrating Dataverse and Power Platform components - Connecting Azure services and APIs |
| Deploy, Monitor, and Optimize AI Agents | - Publishing and deploying copilots - Monitoring performance and analytics - Iterative improvement and lifecycle management |
| Build and Configure AI Agents in Copilot Studio | - Configuring actions, plugins, and connectors - Creating and configuring copilots and topics - Using generative AI and prompt engineering in Copilot Studio |
| Plan and Design Copilot Studio AI Agents | - Selecting Copilot Studio capabilities and architecture approach - Requirements analysis for AI agent solutions - Designing conversation flows and agent behavior |
| Governance, Security, and Compliance | - Environment management in Power Platform - Managing access control and authentication - Data protection and responsible AI practices |
>> Microsoft AB-620日本語版復習指南 <<
今の多くのIT者が参加している試験に、MicrosoftのAB-620認定試験「Designing and Building Integrated AI Agent Solutions in Copilot Studio」がとても人気がある一つとして、合格するために豊富な知識と経験が必要です。MicrosoftのAB-620認定試験に準備する練習ツールや訓練機関に通学しなればまりませんでしょう。Fast2testは君のもっともよい選択ですよ。多くIT者になりたい方にMicrosoftのAB-620認定試験に関する問題集を準備しております。君に短い時間に大量のITの専門知識を補充させています。
質問 # 121
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.
正解：
解説：
Explanation:
Approval stage # Wait for a response and branch according to the decision; Information-collection stage # Wait for a response and capture the submitted inputs.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: An approval is a decision gate. The flow must pause until the reviewer responds, then branch to the appropriate approved, rejected, or other outcome path. Information collection also pauses, but its purpose is to capture supplied values and make them available to later actions in the same run. Sending a request or notification and continuing immediately would break both requirements because downstream processing could occur before the human response exists. The action should have a defined timeout and an escalation or cancellation path so a missing response does not leave the process suspended indefinitely. The flow should store the response, responder identity, timestamp, and any comments needed for audit. Sensitive information should not be requested through an inappropriate channel and should be protected in logs and variables. Testing must cover approval, rejection, corrected information, timeout, and unauthorized-responder cases. This produces a controlled human-in-the-loop design rather than a simple alert that has no effect on execution. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Create a human-in-the-loop agent flow.
質問 # 122
Drag and Drop Question
A company has an existing custom connector that is approved and available in the environment.
A builder wants an agent in Copilot Studio to call the connector during a conversation to retrieve information from an internal system.
To meet the business needs, the solution must meet the following requirements:
- The agent must make the connector available for topic steps.
- The agent must run the connector call with a valid connection.
- The connector call must receive the required input values at runtime.
You need to configure the agent so the custom connector can be used as a tool.
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.
正解：
解説：
Explanation:
Box 1: Add the connector as a tool in the agent.
To make an approved custom connector available for topic steps within Copilot Studio, you must add the connector as a tool in the agent.
In Copilot Studio, actions and custom connectors must be explicitly registered as "Tools" within the agent's capabilities before they can be recognized or called by topics.
Box 2: Create or reuse a connection for the connector
The appropriate action is to create or reuse an existing connection for the custom connector.
Because the connector is already approved and available in your environment, you can simply select it from your tools and link the predefined connection Use connectors in Copilot Studio agents.
Box 3: Map topic variables to the tool inputs
The correct configuration action is to Map topic variables to the tool inputs.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/advanced-connectors
質問 # 123
Two Copilot Studio agents need to delegate tasks to each other directly, with each agent able to advertise its own capabilities to the other. Which two components are required? (Choose two.)
正解：A、B
解説：
The Agent2Agent (A2A) protocol relies on an agent card (capability discovery) and an exposed A2A endpoint so one agent can securely discover and invoke another agent's capabilities.
質問 # 124
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 ensure that every AI-generated response from the agent in Copilot Studio includes a disclaimer that complies with the company's security and governance policies.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
正解：B、E
解説：
[B]
Using prompt modification in the Generative Answers node settings is an excellent and highly effective strategy for embedding compliance disclaimers into your agent's responses.
[A]
Adding a mandatory disclaimer to your greeting message is the best practice for agent governance. You can enforce this by configuring your Greeting System Topic and adding formal
"Output Rules" to the agent's core instructions.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-boost-node
https://www.reddit.com/r/copilotstudio/comments/1pje5fy/how_do_you_handle_ai_disclaimers_in
_copilot/
質問 # 125
A team is preparing to evaluate an agent in Copilot Studio before expanding access to additional users.
The team must choose an evaluation method that meets the following requirements:
Use a fixed set of prepared interactions.
Determine responses against a predefined baseline.
Support consistent comparison across repeated test runs.
You need to determine the evaluation method that satisfies the evaluation requirements.
正解：
解説：
質問 # 126
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