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| Section | Objectives |
|---|---|
| Topic 1: Integrate External Systems and Data Sources | - Connecting Azure services and APIs - Integrating Dataverse and Power Platform components - Using Power Automate for workflow orchestration |
| Topic 2: 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 |
| Topic 3: Governance, Security, and Compliance | - Environment management in Power Platform - Managing access control and authentication - Data protection and responsible AI practices |
| Topic 4: Deploy, Monitor, and Optimize AI Agents | - Iterative improvement and lifecycle management - Publishing and deploying copilots - Monitoring performance and analytics |
| Topic 5: Build and Configure AI Agents in Copilot Studio | - Using generative AI and prompt engineering in Copilot Studio - Creating and configuring copilots and topics - Configuring actions, plugins, and connectors |
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NEW QUESTION # 85
Drag and Drop Question
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:
Box 1: Add the connector as a tool in the agent
To make the custom connector actions available for the agent to invoke, the correct configuration action is to add the connector as a tool in the agent.
Box 2: Create or reuse a connection for the connector
The correct configuration action to ensure authentication is handled at the service level (and not per user) is to create or reuse a connection for the connector.
Service-Level Auth: In Copilot Studio, when you use a custom connector, you must establish a connection that determines how credentials are supplied.
Connection Creation: By creating a connection using a fixed service account or API key-and configuring it to be shared or run under that specific context-the agent authenticates at the system/service level.
Box 3: Map topic variables to the tool inputs
The correct configuration action is to map topic variables to the tool inputs.
When you add a custom connector to an agent in Microsoft Copilot Studio, it functions as a "tool" or an action. To pass specific data-such as conversation context or user details-from the ongoing chat into that connector, you must map the active Copilot Studio topic variables to the input parameters defined by the connector's REST API.
Box 4: Parse the JSON response and assign it to a topic variable
To surface the returned data of the connector to the user in Copilot Studio, the correct configuration action is to parse the JSON response and assign it to a topic variable.
Data Extraction: Custom connectors return raw JSON data from REST APIs.
Variable Storage: Copilot Studio cannot display raw JSON directly to users in a clean way.
User Delivery: You must parse that JSON payload to isolate specific fields and save them into topic variables, which can then be inserted into message nodes for the user to read.
Reference:
https://learn.microsoft.com/en-us/power-platform/release-plan/2024wave2/microsoft-copilot-studio/create-rest-api-copilot-connectors-copilot-studio
NEW QUESTION # 86
A company uses multiple Copilot Studio agents that perform specialized tasks.
You need to configure a Copilot Studio agent in your environment to connect to an external agent.
What should you do?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: An external agent that supports Agent2Agent is connected by supplying its A2A endpoint and the required authentication configuration. The endpoint represents a collaboration interface between independently orchestrated agents, enabling the Copilot Studio agent to delegate a task and receive the partner agent's response. Generative answers cannot call another agent merely because both use generative AI; they retrieve and synthesize from knowledge sources. A Power Platform connector could wrap an ordinary API, but it would not use the specified A2A agent contract and would lose agent-to-agent semantics. Adding the target as indexed knowledge would only make a corpus searchable and would not execute the target agent. The endpoint must be the A2A message endpoint, not just a website or agent-card URL. The builder should give the connection a discriminating description, configure authentication if the endpoint is protected, and validate handoff behavior in the test pane. Production planning should include timeout, failure, logging, and data-sharing boundaries between the two agents. Study Guide alignment: Integrate and extend agents in Copilot Studio > Configure multi-agent collaboration from Copilot Studio > Create a multi-agent solution by using A2A protocol.
NEW QUESTION # 87
A company is building an agent that uses an agent flow to retrieve data from an external system and return structured output.
The company needs to create a flow that the agent can invoke to process requests and return results. To support this business need, the flow must meet the following requirements:
Accept parameters from the agent.
Execute an action to retrieve data from the database.
Ensure the agent receives the relevant output information.
Answer:
Explanation:
Explanation:
1. Create a new agent flow; 2. Define input values; 3. Add the database connector action and configure its connection; 4. Define output values returned to the agent; 5. Test the flow run.
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The flow container must exist before its interface and implementation can be configured. Inputs are defined early so the agent has a typed contract for the values it will pass, such as an account ID or search criterion. The connector action then uses those inputs to query the database through a valid connection. Output parameters are mapped from the connector result so the calling agent receives only the relevant structured values rather than an opaque internal payload. Testing comes last because it validates the completed contract, connection, query, transformation, and returned output together. Omitting output definitions is a common reason an agent receives blank or unusable data even though the connector action itself succeeded. Input and output names should be descriptive, types must agree on both sides, and sensitive fields should be excluded unless genuinely required. After the flow passes direct tests, add or publish it as a tool and verify the end-to-end conversation path, including invalid input, empty-result, authentication, and timeout scenarios. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Create an agent flow; Add input and output parameters.
NEW QUESTION # 88
An agent in Copilot Studio must complete tasks by automating interactions with a legacy desktop application that does not use APIs.
During testing, the builder must confirm that the automation runs in a supported execution context and can inspect how each automation step executes during conversations.
To meet the business needs, the solution must:
* Execute UI automation in a supported, platform-managed environment.
* Provide visibility into how automation steps run during agent conversations.
You need to configure the agent based on the requirements.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
Answer: A,E
Explanation:
The computer use tool enables a Copilot Studio agent to operate graphical interfaces when an application does not expose a suitable API. It uses a computer-using model, virtual mouse, keyboard, and visual reasoning to select controls, enter information, and navigate desktop applications. The builder must configure an eligible Windows execution target, such as a supported Cloud PC or registered machine, and provide clear task instructions, connection details, credentials, and permitted applications.
Execution visibility is provided through the agent's runtime activity information. From the agent's Activity section, the builder can select an individual run and inspect its activity map or transcript. Computer-use testing also provides a step-by-step log and a preview of the actions performed on the configured machine.
This enables the builder to confirm which controls were selected, how the automation progressed, and where failures occurred.
A knowledge source cannot interact with a graphical interface, while a custom connector requires an API.
Publishing makes a completed configuration available to users but does not itself configure UI automation or provide step-level diagnostic visibility.
Relevant study-guide area: Integrate and extend agents in Copilot Studio # Add tools to agents # Configure and monitor computer use for an agent . See Automate web and desktop apps with computer use and Monitor computer use .
NEW QUESTION # 89
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 determine which authentication model should be applied to each Blue Yonder Copilot interaction scenario to comply with the company's security and governance requirements.
Which authentication requirement should you apply to each scenario? To answer, move the appropriate authentication requirements to the correct user scenarios. You may use each authentication requirement 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: Allow anonymous access.
Scenario: Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Box 2: Require customer sign-in using an account.
Scenario: Authentication is required for personal data access (e.g., bookings, loyalty points).
Box 3: Require internal agent sign-in using Microsoft Entra ID.
Scenario: Internal staff: Authenticate via Microsoft Entra ID.
NEW QUESTION # 90
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