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| Section | Weight | Objectives |
|---|---|---|
| Deploy and Monitor Agentic AI Solutions | 20-25% | - Implement error handling and logging - Optimize agent performance - Publish and deploy agent solutions - Configure monitoring and analytics |
| Governance and Best Practices | 10-15% | - Ensure regulatory compliance - Apply responsible AI principles - Implement data privacy and security controls |
| Implement Agentic AI Solutions | 30-35% | - Configure AI agents using Microsoft Copilot Studio - Implement data connections and plugins - Configure security and compliance settings - Set up agent-to-agent communication |
| Design Agentic AI Solutions | 30-35% | - Select appropriate AI models and services - Define agent capabilities and boundaries - Design multi-agent architectures - Identify business scenarios for agentic AI |
>> AB-100 Zertifizierungsantworten <<
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54. Frage
You are designing an AI business solution that contains the following components:
- A Microsoft Power Automate workflow
- A Microsoft Copilot Studio agent
- A Microsoft Dataverse database
- A Microsoft Power Apps app
As part of the application lifecycle management (ALM) process, you plan to package the components, so that they can be deployed to other environments as a group.
You need to recommend a solution that supports versioning, dependencies, and deployments.
What should you include in the recommendation?
Antwort: A
Begründung:
To package your AI business solution components-including the Power Automate workflow, Copilot Studio agent, Dataverse database, and Power Apps app-you should use Microsoft Power Platform solutions.
While GitHub Actions and Azure DevOps are powerful tools for automating the deployment process (CI/CD), Solutions are the actual "containers" or packaging mechanism required to bundle these specific Power Platform assets together so they can be moved as a single unit between environments.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/solutions-overview
55. Frage
Case Study 2 - Contoso, Ltd
Overview
Contoso, Ltd. is a high-tech manufacturing company that uses Microsoft Dynamics 365 Finance.
Dynamics 365 Supply Chain Management, and Dynamics 365 Commerce for its North American operations. The company designs and develops innovative products that have many patents and proprietary technologies. The patents and engineering designs are closely guarded secrets.
Contoso executives want to integrate and adopt AI solutions to help scale the company in preparation for an anticipated period of rapid growth.
The company has multiple legal entities and Azure subscriptions that will be used in the adopted AI solutions.
Requirements
AI Adoption
The following executives will have specific responsibilities in the overall AI adoption:
- Chief Technology Officer (CTO): Select one Dynamics 365 Finance,
Dynamics 365 Supply Chain Management or Dynamics 365 Commerce prebuilt
AI agent and one custom Microsoft Copilot Studio AI agent to prioritize and deploy during the initial AI adoption phase.
- Chief Information Officer (CIO): Ensure that appropriate security
labels are assigned to the data used by the AI agents.
- Chief Financial Officer (CFO): Analyze the return on investment (ROI) for the AI agents being deployed.
- Chief Information Security Officer (CISO): Discover and inventory AI
resources for auditing.
- Chief Executive Officer (CEO): Ensure that all solutions adhere to
industry-standard responsible AI practices.
All AI initiatives and agents will have a detailed business use case, a defined audience profile, and an estimated ROI that will compare the cost savings of the current process against the estimated costs of using the new AI solutions.
The company's research and development (R&D) department already has a custom Model Context Protocol (MCP) server that contains comprehensive product specifications and compliance data.
Prebuilt AI Agent
The CTO has NOT yet selected which prebuilt AI agent to use in Dynamics 365 Supply Chain Management. The CTO wants to view available agent templates to identify which agent will add the most business value.
Depending on which high-priority AI agents are identified, its agent capabilities must be previewed in a discovery meeting with the relevant business operation stakeholders.
Custom AI Agent
Contoso has identified the following custom AI agent requirements:
- The custom AI agent will use data from Dynamics 365 Supply Chain
Management to answer questions for the manufacturing team as a low-code solution.
- The custom AI agent will be accessible from within Microsoft Teams.
- The custom AI agent must be designed to eventually connect to other
agents that can be selected based on their description.
- The topics used in the custom AI agent will be selected based NOT on
a trigger phrase, but on a description of the purpose of the query, to
make the interactions more conversational.
- The custom AI agent must be able to answer questions about product
specifications by using existing technologies. The product
specifications are maintained by the R&D department.
- The custom AI agent must be integrated with and accessible from
Dynamics 365 Supply Chain Management.
- The custom AI agent must be able to use Dynamics 365 Supply Chain
Management business logic that is stored outside of the application.
Analysis, Reporting, and Troubleshooting
Contoso has identified the following analysis, reporting, and troubleshooting requirements:
- The CISO will audit all the AI solutions monthly for compliance and
security.
- The CFO will analyze all the AI solutions quarterly to compare the
estimated ROI against actual measured efficiencies and adoption. The
CFO will use the Copilot Studio agent usage estimator to perform this
analysis.
- The CISO wants to identify how much sensitive data was accessed for a given AI agent run and who accessed the data. Too much sensitive data accessed by a single user might indicate a high security risk.
- The CTO wants to track user feedback on the quality of the AI agent
responses during user interactions with the agents. Consistently poor
feedback will trigger an escalated reengineering discussion.
- The CEO wants a quarterly assessment of all the required metrics for
their specific responsibilities. The tools used for the assessments
must be Microsoft-recommended and must verify reliability,
interpretability, fairness, and compliance.
- The CFO wants to identify how many interactions with the AI agents
are abandoned on a given day as compared to resolved conversations. Too many abandoned sessions might indicate that Copilot Studio credits are being used inefficiently by end users.
What should you recommend to assist the CTO with the prebuilt agent selection process?
Antwort: B
Begründung:
Agent management is the correct tool to use for viewing available agent templates and deciding which AI agent to use within Dynamics 365 Supply Chain Management.
Available Agent Discovery Tools
When working within Dynamics 365 Finance and Operations apps (including Supply Chain Management), the specifically designed interface for these tasks is Agent management.
Agent Management: A dedicated preview feature in Finance and Operations apps that allows users to discover, configure, and manage autonomous AI-powered agents.
Incorrect:
[Not B]
Copilot Studio: While this is the platform used to build and customize agents and track detailed analytics (like thumbs-up/down feedback), it is a standalone low-code tool rather than the primary discovery pane inside the SCM interface.
[Not C]
Lifecycle Services (LCS): Primarily used for environment management, deployments, and updates rather than the day-to-day discovery of specific AI agent templates.
[Not D]
Immersive Home: Typically refers to a broader Microsoft 365 or entry-level experience, not the specialized ERP agent management portal.
Scenario:
Prebuilt AI Agent
The CTO has NOT yet selected which prebuilt AI agent to use in Dynamics 365 Supply Chain Management. The CTO wants to view available agent templates to identify which agent will add the most business value.
The CTO wants to track user feedback on the quality of the AI agent responses during user interactions with the agents. Consistently poor feedback will trigger an escalated reengineering discussion.
Reference:
https://learn.microsoft.com/en-us/dynamics365/copilot/ai-get-started
56. Frage
A company uses a Microsoft Copilot Studio agent to automate tasks in a web app.
During testing, you discover that the automation sometimes fails because of frequent changes to the app's user interface.
You need to recommend a solution to ensure that the agent successfully automates the tasks.
The solution must minimize changes to the agent.
What should you include in the recommendation?
Antwort: D
Begründung:
The Computer Use tool in Microsoft Copilot Studio is specifically designed to remedy automation failures caused by UI changes with minimal manual intervention.
Unlike traditional Robotic Process Automation (RPA), which relies on rigid selectors or fixed coordinates that break when a layout shifts, Computer Use is powered by Computer-Using Agents (CUA). This AI model combines computer vision with advanced reasoning to "see" the screen like a human, allowing it to adapt to interface changes in real-time.
Why Computer Use Fixes UI Fragility
Visual Reasoning: Instead of looking for a specific HTML tag that might change, the agent looks for the visual concept of a button (e.g., "Submit" or a "plus icon").
Real-Time Adaptation: If a button moves from the left side of the screen to the right, the agent simply scans the screen and finds its new location without requiring you to update any code or scripts.
Natural Language Instructions: You describe the task in plain English (e.g., "Log into the portal and download the latest invoice"). If the portal changes its navigation menu, the AI reasons through the new layout to find the invoice link.
Self-Healing Properties: Because the agent makes decisions at each step based on the current visual state, it effectively "self-heals" during execution, overcoming obstacles that would typically crash a legacy bot.
Reference:
https://www.microsoft.com/en-us/microsoft-copilot/blog/copilot-studio/announcing-computer-use-microsoft-copilot-studio-ui-automation
57. Frage
A customer service agent deployed in Copilot Studio is receiving negative feedback from users.
The support team reports that the agent frequently provides incorrect answers about product warranty policies. The team wants to diagnose and resolve the issue.
Which monitoring approach should you recommend?
Antwort: A
Begründung:
Effective agent monitoring starts with analysing conversation transcripts and topic analytics to understand exactly where the agent is failing. By reviewing which topics trigger when warranty questions are asked, you can determine whether the issue is incorrect topic routing, outdated knowledge source content, or poorly designed conversation flows. This diagnostic approach enables targeted fixes rather than wholesale rebuilding.
58. Frage
A company has an AI solution named Solution1 that is deployed to the production environment.
Solution1 uses an Azure OpenAI model to generate marketing emails for existing customers.
During an internal review, you identify that Solution1 creates different emails depending on the customers' traits.
You need to recommend a strategy to mitigate the bias. The strategy must adhere to Microsoft responsible AI principles.
What should you recommend?
Antwort: D
Begründung:
To reduce bias in your Azure OpenAI email generation system while adhering to Microsoft's Responsible AI (RAI) Principles, you should implement a multi-layered approach within your System Instructions.
The goal is to move from generic prompts to specific, constraint-based instructions that enforce Fairness and Inclusiveness.
Reference:
https://whitebeardstrategies.com/blog/designing-inclusive-ai-systems-through-prompting-principles
59. Frage
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