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Microsoft AB-100 認定試験の出題範囲:

トピック出題範囲
トピック 1
  • Deploy AI-powered business solutions: Focuses on deploying, testing, monitoring, and optimizing AI solutions in production. It also includes managing ALM processes, performance monitoring, and ensuring security, governance, and responsible AI compliance.
トピック 2
  • Plan AI-powered business solutions: Focuses on analyzing business requirements and identifying where AI agents and generative AI can improve processes. It also includes defining AI strategy, evaluating ROI, and deciding whether to build, buy, or extend AI components.
トピック 3
  • Design AI-powered business solutions: Covers designing AI agents, Copilot integrations, and intelligent workflows using platforms like Copilot Studio, Microsoft Foundry, and Dynamics 365. It includes planning prompts, connectors, agent behaviors, and solution extensibility.

>> AB-100試験問題 <<

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Microsoft Agentic AI Business Solutions Architect 認定 AB-100 試験問題 (Q66-Q71):

質問 # 66
A financial services company uses Microsoft Dynamics 365 Finance.
Currently, the company ' s support staff manually reviews customer transaction histories to detect potential fraud cases before escalating the cases.
You need to recommend an automation solution for the review process. The solution must ensure that escalations reach a human analyst for final decision making. What should you recommend?

正解:A

解説:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answer is C. Configure a task agent to generate fraud risk scores for the human analyst to review .
This scenario is a classic human-in-the-loop AI business solution use case. The company wants to automate part of the fraud review process, but it also requires that final escalation decisions remain with a human analyst . That means the right solution is not full autonomy. It is decision support .
A task agent that generates fraud risk scores is the best fit because it allows AI to:
* analyze transaction history faster than manual review
* identify suspicious patterns
* prioritize cases
* reduce analyst workload
* preserve human oversight for final judgment
This design aligns with responsible AI and regulated-industry practices. In financial services, fraud detection often involves compliance, risk, and audit requirements. Because of that, the best architecture is usually one where AI assists with triage and recommendation , while a human makes the final decision.
Why the other options are incorrect:
A). Deploy an autonomous agent that closes non-fraud cases automatically This removes too much human oversight. The question explicitly requires that escalations reach a human analyst for final decision making . In fraud workflows, automatically closing cases can create regulatory, legal, and operational risk.
B). Use Microsoft 365 Copilot in Word to automatically finalize fraud detection policies This does not address the operational review process. It is about document productivity, not transaction review automation.
D). Export the data to a data lake for analysis in Microsoft Power BI
This may help reporting and analytics, but it does not directly automate the review-and-escalation workflow.
Power BI is primarily for visualization and analysis, not real-time task-level fraud triage.
Expert reasoning:
When the requirement says:
* automate the review process
* keep a human in final control
* support case escalation
the best answer is usually an assistive agent that scores or classifies risk for human review, not a fully autonomous one.


質問 # 67
A company uses Microsoft Foundry agents.
You need to ensure that an agent can dynamically use external tools at runtime without updating the agent.
What should you include in the solution?

正解:C

解説:
The correct answer is A. a Model Context Protocol (MCP) server.
In Microsoft Foundry agent scenarios, MCP is used to let an agent discover and use external tools dynamically at runtime without requiring the agent itself to be modified each time a new tool or capability is added.
Why this is correct:
MCP standardizes how tools are exposed to agents
It allows the agent to connect to external capabilities in a flexible, runtime-driven way New tools can be made available through the MCP server without rebuilding or updating the core agent definition This directly matches the requirement:
"ensure that an agent can dynamically use external tools at runtime without updating the agent." Why the other options are not correct:
B). a Microsoft Foundry hubA hub is used more for organizing and managing AI resources/projects, not specifically for dynamic runtime tool exposure.
C). Microsoft Copilot StudioCopilot Studio is for building conversational agents and workflows, but the question is specifically about dynamic external tool use in Foundry agents.
D). Azure AI SearchAzure AI Search is for indexing and retrieving knowledge, not for dynamically exposing executable external tools.


質問 # 68
A company plans to implement an AI solution that will contain a Microsoft Copilot Studio agent and a Microsoft Foundry agent. The solution will be stored in a source code repository.
You need to recommend a deployment method for each agent. The solution must meet the following requirements:
A test environment must be used before a deployment to production.
Production must be isolated from development and testing.
The deployment must be repeatable and fully automated.
The solution must NOT require manual intervention.
Which deployment method should you recommend for each agent? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:
Copilot Studio # Use a Microsoft Power Platform deployment pipeline; Microsoft Foundry # Use an Azure DevOps pipeline


質問 # 69
What should you include in the custom Al agent design to meet the R & D product specifications and the compliance information requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:
To expose the data to the agent, create: a custom connector
Add to the agent: the MCP server
The custom agent must answer questions about product specifications and compliance information, and the case study states that the R & D department already has a custom Model Context Protocol (MCP) server containing that information.
The best design is:
create a custom connector to expose that external capability cleanly to the low-code Copilot solution add the MCP server to the agent so the agent can use that external knowledge/tooling source Why this is correct:
The MCP server already exists and contains the needed product-specification and compliance data.
In a Copilot/agent design, you need a way to expose external functionality and data in a reusable, secure way.
A custom connector is the low-code integration mechanism that fits this requirement.
Then the agent can use the MCP server as the connected external capability for answering those questions.
Why the other options are not correct:
Azure AI Bot Service channel is for communication channels, not for exposing this knowledge source.
a custom OData entity is not the right pattern for integrating the existing MCP-based capability.
the Semantic Kernel is a developer orchestration framework, but the requirement emphasizes using the existing MCP technology in a low-code solution.
an event trigger is unrelated to exposing R & D specification/compliance knowledge.
a REST API is too generic here; the scenario specifically points to the existing MCP server.
a tool is close conceptually, but the most direct answer choice tied to the existing R & D technology is the MCP server.


質問 # 70
A company deploys a Microsoft Copilot Studio agent that integrates with a Microsoft Power Automate desktop flow.
You need to recommend a testing solution that meets the following requirements:
Test cases must validate the most recent changes to the agent before the agent is released.
The flow must be validated as part of the agent ' s orchestration.
What should you recommend for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解:

解説:

Explanation:
Validate most recent changes # Run tests against the latest unpublished version of the agent; Validate the flow as part of orchestration # Add the flow to the agent as a tool Why the first selection is correct The requirement says the company must validate the most recent changes to the agent before the agent is released . That means testing must happen on the newest working version that has not yet been published to production.
So the correct recommendation is:
Run tests against the latest unpublished version of the agent
This is the safest and most appropriate pre-release testing pattern because it allows the team to:
* verify recent changes before users see them
* catch regressions early
* validate orchestration logic in a controlled state
* reduce production risk
From an AI business solutions perspective, pre-release testing is critical for Copilot agents because even small changes in prompts, tools, orchestration, or data connections can affect:
* response quality
* workflow behavior
* escalation paths
* compliance behavior
* user trust
Testing unpublished changes ensures that governance and quality assurance happen before release, not after deployment.
Why the second selection is correct
The question also requires that the Power Automate desktop flow be validated as part of the agent ' s orchestration .
That means the flow must participate directly in the agent's runtime action path. The correct way to do that is:
Add the flow to the agent as a tool
When a flow is added as a tool, the agent can invoke it during its orchestration. This allows test cases to validate not only the conversational layer, but also the actual execution of the flow inside the end-to-end agent behavior.
From an agentic AI design perspective, tools are how agents connect reasoning with action. If the flow is meant to be part of orchestration, it must be exposed to the agent in a way that allows the agent to call it during task execution.
That is the correct enterprise pattern for validating integrated behavior.


質問 # 71
......

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