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Microsoft AB-100 Exam Syllabus Topics:
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Microsoft Agentic AI Business Solutions Architect Sample Questions:
What should you configure for the custom Al agent?
- A. generative orchestration
- B. Azure OpenAI reasoning models
- C. Al-assisted evaluators
- D. classic orchestration
Correct Answer: A π³οΈ
Explanation: Only visible for Actual4Exams members. You can sign-up / login (it's free).
You need to recommend a Microsoft Power Platform solution for customer support. The solution must include Al capabilities in Microsoft Power Automate and must meet the following requirements:
* Use a centralized workspace for Al models.
* Generate short overviews from large amounts of unstructured text such as case notes or transcripts, without requiring additional training or coding.
What should you include in the recommendation for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
1. Centralized Workspace for AI Models
In the evolving Microsoft AI ecosystem, Azure AI Foundry (formerly Azure AI Studio) serves as the unified, centralized workspace for developers and organizations to build, manage, and deploy AI models.
Unified Hub: It provides a single location to access the Model Catalog, manage deployments, and perform prompt engineering.
Integration: While AI Builder is the " front-end " for citizen developers in Power Automate, Azure AI Foundry is the foundational " engine room " where the underlying models (including those used by prompts) are managed and governed at an enterprise level.
Scalability: It allows organizations to host their own custom models or utilize industry-leading foundation models (like GPT-4o) which then power the downstream capabilities in the Power Platform.
2. Generating Short Overviews Without Training or Coding
To summarize large amounts of unstructured text like case notes or transcripts without manual effort, AI Builder prebuilt prompts are the specific solution.
AI Builder Prebuilt Prompts: These are ready-to-use GPT-based instructions designed for common business tasks. Specifically, the " AISummarize " prebuilt prompt is engineered to take input text and generate a concise summary automatically.
Zero Training Required: Unlike " Custom Models " which require you to provide sets of historical data to teach the AI, prebuilt prompts leverage pre-trained Large Language Models (LLMs). This meets the requirement of " no additional training or coding. " Ease of Use: In Power Automate, you simply add the " Create text with GPT using a prompt " action and select the prebuilt summary prompt, passing it the text from your case notes or transcripts.
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.
- A. quality of generated answers
- B. session information and session outcomes
- C. engagement, resolution, and escalation rates
- D. survey results
- E. topic usage and topics with low resolution
Correct Answer: A,B π³οΈ
Explanation: Only visible for Actual4Exams members. You can sign-up / login (it's free).
A company has a Microsoft Power Platform environment.
You need to build two agents named Agent1 and Agent2. The solution must meet the following requirements:
* Agent1 must be extendable by using the Semantic Kernel and must connect to multiple business apps and APIs.
* Agent2 must connect directly to data stored in Microsoft Dataverse and must be embeddable in a Microsoft Power Apps canvas a pp.
What should you use to build each agent? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Agent1 # Microsoft Foundry
Agent2 # Copilot in Power Apps
Comprehensive and Detailed Explanation from Agentic AI Topics:
For Agent1, the requirement is that it must be extendable by using Semantic Kernel and connect to multiple business apps and APIs. The best fit is Microsoft Foundry because Foundry-based agents are designed for extensibility and developer-oriented orchestration, including integration patterns that work well with Semantic Kernel and external tools/APIs.
For Agent2, the requirement is that it must connect directly to Microsoft Dataverse and be embeddable in a Power Apps canvas app. The best fit is Copilot in Power Apps, because it is designed for Power Platform- native experiences, works naturally with Dataverse-backed app data, and is intended for embedding AI experiences inside canvas apps.
Why the other options are not the best match:
Azure Logic Apps is for workflow orchestration, not the primary platform for building these agents.
Microsoft Copilot Studio is strong for conversational agents, but the wording here points more directly to Power Apps-native embedding for Agent2 and Semantic Kernel extensibility for Agent1.
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.
Correct Answer:
Explanation:
Copilot Studio # Use a Microsoft Power Platform deployment pipeline; Microsoft Foundry # Use an Azure DevOps pipeline
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