Free Microsoft AB-620 Practice Test & Real Exam Questions

  • Exam Code/Number: AB-620
  • Exam Name/Title: Designing and Building Integrated AI Agent Solutions in Copilot Studio
  • Certification Provider: Microsoft
  • Corresponding Certification: Microsoft Certified: AI Agent Builder Associate
  • Exam Questions: 101
  • Updated On: Aug 09, 2026
Drag and Drop Question
You are configuring an agent in Copilot Studio for an organization. The organization uses Microsoft Dataverse, Dynamics 365, and SharePoint Online.
The agent must retrieve information from enterprise systems and internal documents. The agent must meet the following requirements:
- Must retrieve the current balance of a customer account stored in
Dataverse.
- Must retrieve the real-time shipping status of an order that updates
throughout the day in Dynamics 365.
- Must answer questions based on the content of a static PDF policy
document.
- Must provide a welcome message that does NOT depend on enterprise
data.
You need to configure the agent to meet the requirements.
How should the agent retrieve the data? To answer, move the appropriate solutions to the correct requirements. You may use each solution 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.
Correct Answer:

Explanation:
Box 1: Connect to a Power Platform connector
To enable your Copilot agent to fetch specific, real-time structured data (such as a customer's current balance) directly from Dataverse or Dynamics 365, you should connect to a Power Platform connector (or use native Dataverse plugins/tools).
Box 2: Connect to a Power Platform connector
Real-Time Data Access: Dynamics 365 data resides in Microsoft Dataverse. Power Platform connectors (like the Dataverse connector) fetch data live from the source, ensuring the shipping status is perfectly accurate and updated throughout the day.
Box 3: Upload a file to Agents Knowledge Base.
Box 4: Create a manual response in the topic.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-copilot-studio
https://www.matthewdevaney.com/copilot-studio-change-the-agent-welcome-message/
You are designing an agent that must reason over multiple tools and decide autonomously which tool to invoke based on user intent, rather than following a fixed topic sequence. Which Copilot Studio capability should you use?
Correct Answer: A Vote an answer
Explanation: Only visible for Pass4Leader members. You can sign-up / login (it's free).
A company is configuring generative answers for an agent in Copilot Studio agent.
The agent must use Azure AI Search to retrieve enterprise content, and all responses must be generated by a Microsoft Foundry model.
The agent sometimes generates answers that are not grounded in Azure AI Search content. The company requires that the agent only generate responses when relevant indexed content is retrieved.
You need to configure the agent so that its generative answer behavior meets the organization's requirements.
What should you do?
Correct Answer: B Vote an answer
Explanation: Only visible for Pass4Leader members. You can sign-up / login (it's free).
Case Study 2 - Fabrikam Inc.
Background
Fabrikam Inc. is a Canada-based manufacturer with a growing service organization that supports field technicians and internal operations teams. Fabrikam Inc. plans to launch a new internal agent solution named Operations Concierge to reduce time spent searching policy content, retrieving operational metrics, and executing routine transactions.
The agent will be used by three groups:
- Service coordinators who triage incoming service requests
- Field technicians who need guided procedures and parts availability
- Operations managers who monitor KPIs and exceptions
The agent solution must work in real-world operational conditions. Users often ask questions mid- call with a customer or while coordinating parts shipments. The agents require quick, reliable outcomes. As a result, Fabrikam Inc. requires the solution to:
- Provide grounded answers with traceability when it provides guidance.
- Retrieve real-time metrics when users ask for operational status.
- Execute authenticated updates when users initiate a flow (such as creating a parts request).
Fabrikam Inc. also expects the solution to be maintained by multiple makers and developers across the year. The company has experienced duplicated logic and inconsistent behavior across different agents. This project emphasizes reuse, governance, and maintainability across teams.
Current environment
Fabrikam Inc. runs three Microsoft Power Platform environments for agent development and release: Dev, Test, and Prod.
The team plans to build the agent and validate it in Dev and Test, then promote to Prod by using a controlled release process that supports repeatable deployments.
Fabrikam Inc. already has two assets the team wants to reuse:
- A partially completed Copilot Studio agent named Service Desk Agent, used by IT to create internal tickets and route requests
- A Microsoft Foundry agent created by a central AI team that performs specialized summarization and classification for long-form text (for example, summarizing call transcripts into an incident narrative) Fabrikam Inc. also has operational and knowledge data sources:
- A curated policy library (internal SOPs, service warranty rules, escalation criteria, and standard operating procedures)
- A set of indexed documents and procedures in an Azure AI Search service that supports vector search for the policy library
- A Microsoft Fabric workspace that includes a semantic model used by operations leadership for reporting Business requirements Fabrikam Inc. requires Operations Concierge to meet the following business requirements:
- Traceability requirement: When the agent provides policy guidance or procedural recommendations, users must be able to see where the answer came from.
- Metrics requirement: When users ask about service performance (backlog, SLA risk, parts shortages, dispatch delays), the solution must return up-to-date metrics in a structured format that operations managers can use in weekly reviews.
- Transaction requirement: The solution must support authenticated updates initiated during conversations, including creating a parts request and updating a service case status.
In addition, Fabrikam Inc. wants to avoid duplicating common assets across agents:
- The team must reuse the same set of escalation topics, MCP tool definitions, and a standard safety disclaimer across three different agents.
- Only the platform engineering group as allowed to edit shared assets. However, all agent authors must be able to use them.
Technical requirements
The Fabrikam Inc. solution architecture uses a multi-agent approach so that specialist responsibilities are isolated and can evolve independently.
The Operations Concierge (primary agent) must coordinate the following specialist capabilities:
- Policy and procedure Q&A: Use an enterprise knowledge source that supports indexed retrieval across the curated policy library and service procedures.
- Operational metrics: Delegate metric queries to a Fabric Data Agent that reads governed business data through the Fabric semantic model.
- Authenticated updates: Use tools exposed by an existing internal Model Context Protocol (MCP) server that provides transactional operations for the service organization.
- Specialized processing: Delegate summarization and classification requests to an existing Microsoft Foundry agent.
Fabrikam Inc. will onboard two MCP servers as tools:
- PartsOps MCP server: exposes tools for parts availability checks and parts request creation.
The server requires per-user authentication because actions must be traceable to the requesting user.
- WarrantyRules MCP server: exposes a read-only tool for validating warranty coverage. The server uses an API key shared by the agent team.
Fabrikam Inc. has also defined a collaboration requirement with the existing Service Desk Agent:
- The primary agent must delegate IT-specific requests to the existing Service Desk Agent rather than reimplement ticket creation logic.
Finally, Fabrikarn Inc. plans to support a partner integration:
- For shipment tracking inquiries, Fabrikam Inc. will delegate to a partner-provided agent that is only available through a standardized agent-to-agent endpoint.
Issues and constraints
During early testing, Fabrikam Inc. found three recurring problems:
- Makers are copying and modifying the same components across agents, resulting in inconsistent disclaimers and duplicated tools.
- Users can obtain a correct answer, but the response is not consistently traceable to a source when the agent uses knowledge.
- The primary agent can route some requests, but specialist capabilities are not consistently delegated (for example, some metric questions are answered generatively instead of being routed to the Fabric Data Agent).
You are part of the engineering team responsible for correcting the design and configuration to meet the preceding requirements and constraints.
Drag and Drop Question
You need to connect Operations Concierge to Fabrikam Inc.'s Azure AI Search knowledge index while complying with security requirements.
Which configuration should you use 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.
Correct Answer:

Explanation:
Box 1: Select the service principal as the authentication type
Ensure the Azure AI Search connection complies with the governance requirement for authenticated access.
Scenario:
A set of indexed documents and procedures in an Azure AI Search service that supports vector search for the policy library Box 2: Provide the Azure Search Endpoint URL in the connection details.
Ensure policy and procedure Q&A uses the required curated, indexed enterprise knowledge source.
Box 3: Provide the Azure Search Endpoint URL in the connection details.
Ensure the connection targets the Azure AI Search service instance that stores the indexed policy documents.
The best action to take is to Provide the Azure Search Endpoint URL in the connection details.
When connecting a Copilot agent to an external knowledge source like Azure AI Search, establishing the connection requires identifying the specific service host. Providing the Azure AI Search Endpoint URL ensures that the underlying connection infrastructure explicitly targets and authenticates against your specific Azure AI Search service instance. Once this service-level connection is validated, you are prompted in the next step to select or enter the specific index containing your documents.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-azure-ai-search
A company needs an agent in Copilot Studio to complete tasks by interacting with a legacy desktop application that does not use APIs. The builder needs to validate that UI automation can run in the supported execution context and needs a way to inspect how the automation behaves during testing conversations.
To meet the business needs, the solution must meet the following requirements:
- Enable the agent to perform UI automation against the legacy
application.
- Inspect execution details for the automation during 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.
NOTE: Each correct selection is worth one point.
Correct Answer: A,E Vote an answer
Explanation: Only visible for Pass4Leader members. You can sign-up / login (it's free).
Drag and Drop Question
You run the same fixed test set three times in Copilot Studio.
During evaluation, you observe the following:
- The same interaction fails in all three runs.
- Score values range from 0.58 to 0.61.
- The reasoning states that the response partially matches the expected answer.
- The knowledge source that is used is internal documentation.
- No tools are invoked.
You need to determine which conclusions are supported based on the evaluation results.
Which conclusions should you make? To answer, move the appropriate conclusions to the correct evaluation results. You may use each conclusion 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.
Correct Answer:

Explanation:
Box 1: A pattern failure across repeated runs.
The correct conclusion concerning evidence of a recurring issue is a) a pattern failure across repeated runs.
When the exact same interaction fails across three repeated runs, it establishes a systemic, predictable pattern rather than an isolated, one-time anomaly.
Box 2: The response partially matches the expected answer.
Based on the evaluation criteria in Microsoft Copilot Studio, the most definitive and direct conclusion that can be made concerning response quality is that the response partially matches the expected answer.
Direct Evidence: The evaluation results explicitly state in the reasoning that the "response partially matches the expected answer." This directly provides a qualitative conclusion regarding the quality of the generated response.
Score Alignment: The semantic similarity or quality score values ranging from 0.58 to 0.61 align with a partial match. In AI evaluation metrics, a perfect match is represented by 1.0, while values in the 0.6x range indicate that the core context was captured but lacked full completeness or exactness.
Box 3: Use of a connected knowledge source during the interaction
Because generative AI outputs are non-deterministic, running the same test set across a dynamic environment can yield varying scores. In Microsoft Copilot Studio, observing scores consistently between 0.58 and 0.61 points to a fundamental limitation with the underlying knowledge source.
The evaluation points to option use of a connected knowledge source during the interaction.
Because no tools are invoked, the agent heavily relies on generative search (retrieval-augmented generation) over internal documentation. The score range and reasoning indicate that the agent successfully retrieves a document but relies on a probabilistic model to paraphrase or assemble the response, which results in a "partial match" rather than an exact extraction.
Incorrect:
In contrast, specific underlying causes require explicit tool invocations or system error logs to diagnose, which are not present here.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/analytics-agent-evaluation-results