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92. Frage
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
A company has a Microsoft Dynamics 365 Sales environment that has Microsoft Copilot enabled.
You need to customize Copilot by tailoring how opportunity summaries are generated or how they are presented to users.
Solution: You configure AI Builder lead scoring models to influence opportunity summaries.
Does this meet the goal?
Antwort: B
Begründung:
Correct:
* You add fields to the opportunity summary.
Incorrect:
* You build Microsoft Power Automate flows to trigger customized Copilot summaries.
* You configure AI Builder lead scoring models to influence opportunity summaries.
Note:
To customize Microsoft Copilot opportunity summaries and incorporate AI Builder lead scoring data, you must configure the specific fields Copilot uses to ground its generative AI outputs.
By default, Copilot for Sales generates summaries using a set of predefined fields. To "influence" these summaries with scoring data, you need to add the predictive score and grade fields to the Opportunity summary configuration.
Step-by-Step Configuration
Switch Area: In the Sales Hub app, select the Change area menu in the bottom-left corner and choose App Settings.
Navigate to Copilot: Under General Settings, select Copilot.
Select Entity: Choose the Opportunities tab.
Add Fields:
Click Add fields.
Select the checkboxes for the fields you want to include.
You can select out-of-the-box, custom, and related table fields.
Save: Click Add and then Save your changes to update the summary configuration.
Reference:
https://learn.microsoft.com/en-us/dynamics365/sales/copilot-configure-summary-fields
93. Frage
What should you configure for the custom Al agent?
Antwort: D
Begründung:
The custom AI agent must select topics based on a description of the purpose of the query, rather than relying on fixed trigger phrases. That is exactly the scenario where generative orchestration is the right configuration.
Why B is correct:
It enables the agent to choose the best topic, tool, or action based on the semantic meaning of the user's request It supports more conversational interactions It aligns directly with the requirement that topic selection should not depend on trigger phrases Why the other options are not correct:
A). Azure OpenAI reasoning models concerns model capability, not topic-routing behavior in Copilot Studio C). classic orchestration relies more on predefined topics and trigger phrases D). AI-assisted evaluators are for assessment/testing, not runtime orchestration
94. Frage
A company plans to implement an Al business solution for a consumer goods company.
You need to create agents that meet the following requirements:
* Orchestrate the sales order fulfillment and shipping of goods to customers.
* Analyze historical data and trends to replenish stock.
Which type of agent should you use for each requirement? To answer, drag the appropriate agent types to the correct requirements. Each agent type 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.
Antwort:
Begründung:
Explanation:
This question separates two different kinds of agent behavior.
For orchestrating sales order fulfillment and shipping, the best fit is an Autonomous agent. That requirement involves coordinating multiple steps, making decisions across a process, and driving execution across a workflow with limited manual intervention. Autonomous agents are designed for this kind of end-to-end orchestration.
For analyzing historical data and trends to replenish stock, the best fit is a Task agent. This requirement is more focused and bounded: analyze data, identify patterns, and support a specific business function. That aligns with a task-oriented agent rather than a broad orchestration agent.
Why Prompt-and-response is not the best answer here:
It is better suited for direct user query/answer interactions
It is not the strongest fit for process orchestration or structured business analysis workflows
95. 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 CEO with their specific responsibilities?
Antwort: C
Begründung:
Scenario: 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.
To ensure your Microsoft Dynamics 365 AI agent meets quarterly compliance and ethical standards, the Responsible AI (RAI) Dashboard in Azure Machine Learning is the primary recommended tool.
Microsoft recommends aligning quarterly assessments with their Responsible AI Standard v2, which focuses on six core principles: fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai-dashboard
96. Frage
Hotspot Question
You are designing an AI strategy for Microsoft Dynamics 365 finance and operations apps. You are evaluating the use of Microsoft Copilot Studio to provide in-app help and guidance based on generative AI general knowledge.
You need to recommend which knowledge sources to include in the generative help and guidance agent. The solution must minimize the risk of generating inaccurate responses.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Antwort:
Begründung:
Explanation:
Box 1: Must be uploaded to the agent
Custom knowledge sources
Box 2: Must be enabled for the agent
AI general knowledge
To implement a generative AI agent for in-app help in Dynamics 365 Finance and Operations while minimizing inaccuracies, you must configure the agent in Microsoft Copilot Studio by uploading specific knowledge sources and enabling general AI knowledge.
1. Upload Custom Knowledge Sources
To ensure the agent provides accurate, organization-specific guidance, upload your internal documentation directly to the agent
2. Enable General AI Knowledge
To allow the agent to use its own broad generative AI knowledge for general inquiries:
Open Microsoft Copilot Studio and select the Dataverse environment linked to your Finance and Operations apps.
Navigate to Agents and open the specific agent named Copilot for finance and operations apps.
On the Overview tab, find the Knowledge section and set Allow the AI to use its own general knowledge to Enabled.
Publish the changes to make this capability available in the D365 F&O sidecar.
Reference:
https://arpideas.com/en/articles/knowledge-hub/building-smart-ai-agents-with-microsoft-copilot- studio
97. Frage
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