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| Section | Weight | Objectives |
|---|---|---|
| Build and extend agents in Copilot Studio | 40–45% | - Implement advanced capabilities
|
| Test, deploy, and manage agents | 20–25% | - Test and validate agent performance
|
| Plan and configure agent solutions | 30–35% | - Plan an agent solution
|
>> AB-620 Exam Questions And Answers <<
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NEW QUESTION # 76
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 configure the agent in Copilot Studio to meet Blue Vender's Responsible AI and data protection requirements.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Scenario: Problem statement: The agent must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
Step 1: Define Data Loss Prevention (DLP) policies
Security and compliance must be established at the foundation level. Admins use the Power Platform admin center to configure DLP policies. This establishes environmental guardrails by restricting unauthorized data connectors or preventing the agent from leaking sensitive data.
Step 2: Add custom prompt modifications
Once the environment is secure, the maker configures the specific behavior of the agent. Custom prompt modifications and agent instructions shape the tone, define conversational topics, and establish explicit boundaries for the generative model (e.g., instructing the model to strictly stay within its knowledge base).
Step 3: Conduct adversarial testing
This is the final evaluation phase before deployment. After the guardrails and custom prompts are in place, you simulate real-world attacks (such as jailbreaks, prompt injections, or malicious user inputs) to verify that the agent reliably adheres to your corporate guidelines and Microsoft's Responsible AI standards.
Reference:
https://learn.microsoft.com/en-us/troubleshoot/power-platform/copilot-studio/generative-answers/agent-response-filtered-by-responsible-ai
NEW QUESTION # 77
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.
An agent uses a flow that calls an external service which can occasionally fail or time out.
When a failure occurs, the agent must meet the following requirements:
- Must not terminate silently.
- Must send a notification containing the error details.
You need to configure the agent flow so that failures are handled in a controlled and predictable way.
Solution: Configure run after conditions for failure paths.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Configure run after conditions for failure paths.
You should configure the "Run after" conditions in Power Automate (the underlying flow engine) to handle these failures in a controlled and predictable way.
By default, a cloud flow step only runs if the previous step is successful. If your external service fails or times out, all subsequent steps will normally skip, causing the flow to fail silently from the perspective of the Copilot Studio agent.
How to Configure the Flow for Failure Handling
To meet your requirements, you need to create a parallel or sequential failure path using the following steps:
1. Add your Notification Action
2. Configure "Run After" Settings
Incorrect:
* Retry the failing action without handling failure.
* Send a notification with relevant error details.
Reference:
https://www.matthewdevaney.com/3-power-automate-error-handling-patterns-you-must-know/
NEW QUESTION # 78
A company uses an agent flow that calls a connector action. The flow sends an administrative notification if the action fails or times out.
Administrators require the following configuration to help troubleshoot and manage failures:
- Handle failure and timeout outcomes explicitly.
- Continue execution after a failure is handled.
- Avoid retrying the failed action automatically.
You need to configure the agent flow so that failures are handled in a controlled and predictable way.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
To handle failures and timeouts explicitly without automatic retries while ensuring the flow continues, take these two configuration steps in the Power Automate designer:
[D] Configure Run After settings on the notification/recovery step to trigger on "has failed" and
"has timed out" status options from the primary connector action.
[B] Scope Actions: Grouping your connector action and its immediate steps inside a Scope action allows you to centrally manage errors. You can set the subsequent administrative notification to run only if the entire Scope fails or times out. This satisfies the requirement to handle failure and timeout outcomes explicitly in a clean, predictable way Reference:
https://d365demystified.com/2022/01/20/try-catch-error-handling-using-scope-in-power-automate/
NEW QUESTION # 79
A company has an approved custom connector that uses a REST API for an internal system.
An agent in Copilot Studio must call this connector during conversations to retrieve or update data.
To meet the business needs, the solution must meet the following requirements:
Make the connector actions available for the agent to invoke.
Ensure authentication is handled at the service level, not per user.
Pass conversation context into the connector when it is called.
Surface the returned data of the connector to the user in the conversation.
You need to configure the agent and the connector action to meet the requirements.
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:
Requirement
Correct configuration
Make connector actions available for the agent to invoke.
Add the connector as a tool in the agent.
Handle authentication at the service level, not per user.
Create or reuse a connection for the connector.
Pass conversation context into the connector when called.
Map topic variables to the tool inputs.
Surface the connector's returned data to the user.
Parse the JSON response and assign it to a topic variable.
Adding the approved connector as an agent tool exposes its defined REST operations to Copilot Studio. The tool can then be called explicitly from a topic or selected dynamically by generative orchestration, depending on its configuration.
A connector connection stores the authentication configuration required to call the underlying service. Among the provided choices, creating or reusing that connection is the correct service-authentication action. For strict service-level authentication, the tool must additionally be configured under Credentials to use with Maker- provided credentials . Creating a connection alone does not guarantee this behavior if the tool remains configured to use end-user credentials.
Topic variables containing conversation context-such as a customer identifier, ticket number, or requested operation-are mapped to the connector tool's input parameters. This ensures the REST request receives values collected earlier in the conversation.
When the connector returns structured JSON, the relevant values must be parsed and stored in a topic variable. That variable can then be referenced in a message, adaptive card, or subsequent topic node to present the returned information to the user.
Relevant study-guide area: Integrate and extend agents in Copilot Studio # Add tools to agents # Add a tool by using an existing custom connector . See Use connectors in Copilot Studio agents and Add tools to custom agents .
NEW QUESTION # 80
You need to plan how Fabrikam Inc. will reuse shared components across multiple agents while limiting who can change the shared components in Copilot Studio Lite.
Which approach should you use for each requirement? To answer, move the appropriate components to the correct requirements. You may use each component 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:
NEW QUESTION # 81
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