Microsoft - AB-100 - Agentic AI Business Solutions Architect–High Pass-Rate New Test Answers

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Microsoft AB-100 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Agentic AI Business Solutions Architect
Exam Number:AB-100
Passing Score:700 (out of 1000)
Certificate Validity Period:1 year (for recertification)
Exam Format:Scenario-based, Multiple choice
Real Exam Qty:Around 40-50 questions
Related Certifications:Microsoft Applied Skills
Exam Duration:50 minutes
Exam Price:USD $85
Available Languages:English
Sample Questions:Microsoft AB-100 Sample Questions
Exam Way:Online proctored exam
Pre Condition:Basic understanding of Microsoft Copilot, Azure AI services, and general AI/ML concepts recommended
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/applied-skills/agentic-ai-business-solutions-architect/

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Our AB-100 study guide has become a brand for our candidates to get help for their exams. Because our AB-100 learning materials contain not only the newest questions appeared in real exams in these years, but the most classic knowledge to master. Besides, it is unavoidable that you may baffle by some question points during review process of the AB-100 Exam Questions, so there are clear analysis under some necessary questions.

Microsoft AB-100 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 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.
Topic 3
  • 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.

Microsoft Agentic AI Business Solutions Architect Sample Questions (Q84-Q89):

NEW QUESTION # 84
A company plans to deploy a Microsoft Copilot Studio agent to enhance customer support.
The company stores customer data across ServiceNow, Microsoft Dynamics 365 Finance, Dynamics 365 Supply Chain Management, and Excel files in SharePoint Online.
You need to recommend a solution to ensure that the agent can deliver accurate and timely responses.
What should you recommend?

Answer: B

Explanation:
Microsoft Power Platform connectors are the best fit because Copilot Studio agents can use connectors to reach systems such as ServiceNow, Dynamics 365, and SharePoint-backed content, which helps the agent respond using the most current enterprise data.
Connectors let the agent call external systems and retrieve live data rather than relying on a static indexed copy, which is important for both accuracy and timeliness. Microsoft's documentation explicitly includes Microsoft services like SharePoint and Dynamics 365 among supported connector scenarios, and ServiceNow is also a common integration target for Copilot Studio agents.
Reference:
https://learn.microsoft.com/en-us/microsoft-365/copilot/extensibility/overview-copilot-connector
https://learn.microsoft.com/en-us/microsoft-copilot-studio/customer-copilot-servicenow
https://learn.microsoft.com/en-us/microsoft-copilot-studio/advanced-connectors


NEW QUESTION # 85
A company has two Microsoft Power Platform environments named Devi and Prodi. A Microsoft Copilot Studio agent named Agent1 is built into a solution in the Devi environment.
You plan to deploy Agent1 to Prodi.
You need to make Agent1 available to the users in Prodi. The solution must minimize administrative effort.
What should you do?

Answer: D

Explanation:
Because Agent1 is built into a solution in the Dev1 environment and must be deployed to Prod1 with minimal administrative effort, the recommended ALM approach is to export the solution as a managed solution and import it into production.
Why A is correct:
Managed solutions are the standard choice for production deployment
They support cleaner governance and controlled changes in the target environment They minimize manual recreation and reduce admin overhead compared with rebuilding the agent Why the other options are not correct:
B). Export as an unmanaged solution is more appropriate for further development, not controlled production rollout C). Create a new agent manually in Prod1 increases effort and introduces inconsistency risk D). Share Agent1 with users in Prod1 does not deploy the solution into that separate environment


NEW QUESTION # 86
A company uses Microsoft 365 and Dynamics 365
You need to recommend a solution lo automatically summarize email threads, generate suggested replies in Microsoft Outlook, and provide meeting preparation summaries that include relevant customer relationship management (CRM) data.
Solution: You recommend Microsoft 365 Copilot for Sales.
Does this meet the goal?

Answer: A


NEW QUESTION # 87
Drag and Drop Question
A company has an ecommerce support portal that uses Microsoft Dataverse.
You are designing a Microsoft Copilot Studio agent for the portal. The agent must meet the following requirements:
- Respond with a default help message when the user input is unclear.
- Initiate external processes, such as retrieving the order status,
when users make specific requests.
Generative orchestration will be enabled for the solution.
You need to recommend a feature for each requirement.
What should you recommend? To answer, drag the appropriate features to the correct requirements. Each feature may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 88
A company has a Microsoft Copilot Studio agent that provides answers based on a knowledge base for customer support.
Users report that, occasionally, the agent provides inaccurate answers.
You need to use metrics from the Analytics tab in Copilot Studio to identify the cause of the inaccuracies.
Which two options should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: A,E

Explanation:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answers are B. session information and session outcomes and E. quality of generated answers .
This scenario is focused on a knowledge base-driven Copilot Studio agent where users report that the agent sometimes gives inaccurate answers . The question asks which Analytics tab metrics should be used to identify the cause of those inaccuracies.
That means you need metrics that help you examine:
* how the answer was generated
* what happened in the conversation when the bad answer occurred
Why E. quality of generated answers is correct
This is the most direct metric for this scenario.
Because the agent is answering from a knowledge base , the problem is tied to the quality of the generated response itself. The quality of generated answers metric helps assess whether the generated responses are relevant, useful, and accurate enough for the user's request.
From an AI business solutions perspective, this metric is essential because it helps diagnose problems such as:
* weak grounding from the knowledge source
* irrelevant retrieval
* poor answer formulation
* hallucination-like behavior
* mismatch between user question and available source content
If the issue is inaccurate answers, the first place to investigate is the quality signal tied to generated answers.
Why B. session information and session outcomes is correct
To find the cause of inaccuracies, you also need to inspect the broader conversational context. Session information and session outcomes help you see:
* what the user asked
* how the agent responded
* whether the conversation was resolved
* whether the user abandoned, escalated, or retried
* where the conversation broke down
This is important because an inaccurate answer may not come only from poor generation quality. It may also come from:
* the way the user phrased the request
* lack of sufficient grounding context
* repeated failed attempts in a session
* escalation after an unhelpful answer
* patterns in unsuccessful conversations
In other words, quality of generated answers tells you about answer quality, while session information and outcomes help you understand the operational context in which those inaccuracies appear.
Together, these two give the strongest diagnostic view.
Why the other options are incorrect
A). survey results
Survey results can tell you whether users were happy or unhappy, but they do not directly help identify the cause of inaccurate knowledge-based responses. They are more of a feedback signal than a root-cause metric.
C). topic usage and topics with low resolution
This is more relevant for agents built around explicit topics and topic flows. The scenario specifically describes an agent that provides answers based on a knowledge base , so generated-answer analytics are more appropriate than topic-resolution analysis.
D). engagement, resolution, and escalation rates
These are useful high-level operational KPIs, but they are not the best metrics for diagnosing why answers are inaccurate. They show outcome trends, not the direct cause of answer-quality issues.


NEW QUESTION # 89
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