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| Section | Objectives |
|---|---|
| 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 |
| Integrate External Systems and Data Sources | - Using Power Automate for workflow orchestration - Connecting Azure services and APIs - Integrating Dataverse and Power Platform components |
| Governance, Security, and Compliance | - Environment management in Power Platform - Data protection and responsible AI practices - Managing access control and authentication |
| Plan and Design Copilot Studio AI Agents | - Requirements analysis for AI agent solutions - Selecting Copilot Studio capabilities and architecture approach - Designing conversation flows and agent behavior |
| Deploy, Monitor, and Optimize AI Agents | - Publishing and deploying copilots - Monitoring performance and analytics - Iterative improvement and lifecycle management |
The online AB-620 practice exam has all specifications of the desktop software. It is compatible with Chrome, Firefox, MS Edge, Safari, Opera, etc. The Designing and Building Integrated AI Agent Solutions in Copilot Studio (AB-620) practice exam will save your progress and give you an overview of your mistakes, which will benefit your overall preparation. All operating systems support this Designing and Building Integrated AI Agent Solutions in Copilot Studio (AB-620) practice test.
NEW QUESTION # 68
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A company is configuring an agent in Copilot Studio that uses a generative answers node inside multiple topics.
The company requires responses to meet the following requirements:
- Must use an executive summary format.
- Must apply only within a specific topic.
- Must continue using configured knowledge sources.
- Must comply with connector security controls.
You need to configure a custom prompt to meet the formatting requirements.
Solution: Remove the generative answers node and rely only on the custom prompt to produce formatted responses.
Does the solution meet the goal?
Answer: B
Explanation:
Correct:
* Create a custom prompt tool in the specific topic that instructs the model to respond using an executive-summary structure.
To fulfill all the requirements in the best way, you must configure the custom instructions directly inside the specific Generative Answers node properties within that targeted topic.
By default, editing custom instructions at the global agent level or the Conversational boosting system topic applies globally. To scope formatting changes to only one topic while keeping configured data sources and security intact, you must override the instructions at the node level.
Incorrect:
* Add instructions in the custom prompt tool to restrict connector access during runtime.
* Configure the custom prompt tool at the topic level so that other topics are not affected.
* Remove the generative answers node and rely only on the custom prompt to produce formatted responses.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-boost-node
NEW QUESTION # 69
A team is preparing to evaluate an agent in Copilot Studio before expanding access to additional users.
The team must select 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 choose an evaluation method that meets the requirements.
What should you do?
Answer: D
Explanation:
A standardized evaluation matrix is the appropriate choice because it establishes fixed test inputs, expected responses, and consistent scoring criteria. In Copilot Studio, this approach is implemented by creating a reusable test set containing prepared test cases and applying appropriate evaluation methods to each case.
The predefined baseline can consist of expected answers, required keywords, expected tool usage, or custom quality criteria. Depending on the required precision, the team can use exact match, text similarity, compare meaning, keyword match, tool-use, or custom evaluation methods. Copilot Studio records the generated response and evaluates it against the configured expectation, producing repeatable scores and pass-or-fail results.
The same test set can be executed multiple times and the resulting runs compared. This provides an objective way to detect regressions after changes to instructions, topics, knowledge sources, tools, or models. A limited live pilot measures production outcomes but does not provide tightly controlled inputs. Manual transcript reviews and relying on a previous run are subjective and do not establish repeatable evaluation criteria.
Relevant study-guide area: Test and manage agents # Evaluate agent performance # Create a test set, choose an evaluation method, and review test results . See About agent evaluation , Choose evaluation methods , and Run evaluations and view results .
NEW QUESTION # 70
A company must enable an agent in Copilot Studio to execute operations exposed by an external MCP server.
The MCP server publishes callable tools and requires authentication.
The agent must be able to invoke MCP tools during conversations.
You need to configure MCP tools so the agent can execute MCP tool calls.
What should you do?
Answer: A
NEW QUESTION # 71
A company is building an agent in Copilot Studio.
The agent must meet the following requirements:
Responses must be grounded in approved internal content.
The agent must be able to retrieve information from configured data sources in a topic.
You need to configure the agent so that topic responses are grounded from custom data sources.
What should you configure?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A generative answers node inside the topic is the correct place to retrieve from configured knowledge sources for that specific conversational path. The node can use the user's message as input, search designated sources, and generate a grounded response from the retrieved content. Topic-level sources can override the broader agent-level set, which is useful when the topic must restrict itself to approved data. A custom prompt that merely instructs the model to use company information does not create or enforce a retrieval connection. Increasing the response limit affects length, not grounding. Analytics measures usage after the fact and cannot supply knowledge. Adding SharePoint only at agent level is unnecessarily narrow and would not satisfy the requirement for custom sources configured within the topic. The builder should enable Search only selected sources when strict scoping is required and turn off general knowledge if no ungrounded fallback is allowed. Testing should inspect both the answer and the resource details to confirm that the intended source supplied the evidence. Study Guide alignment: Plan and configure agent solutions > Configure topics > Configure generative answers node; Configure advanced agent responses with custom knowledge sources.
NEW QUESTION # 72
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: A,C
Explanation:
Under Compliance and Security, the requirements state: "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." Setting this up at the system level ensures broad, consistent compliance without violating the constraint against manual topic-level edits.
Under Compliance and Security, the case study explicitly states: "Power Platform DLP policies must be enforced to block unauthorized data flows." DLP (Data Loss Prevention) policies are environment-level safeguards configured before deployment to restrict data movement between custom/REST connectors and non-compliant channels/destinations.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/publication-fundamentals-publish-channels
https://learn.microsoft.com/en-us/microsoft-copilot-studio/advanced-dlp
https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-generative-answers
NEW QUESTION # 73
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