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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design AI-powered business solutions | 30% | - Agent and solution design
|
| Topic 2: Plan AI-powered business solutions | 25% | - AI strategy and requirements analysis
|
| Topic 3: Deploy AI-powered business solutions | 45% | - Security, governance, and ALM
|
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問題 #95
You use Microsoft Copilot Studio analytics to analyze the performance of a deployed Copilot Studio agent.
You need to identify which performance metrics to use to measure the following:
* The percentage of engaged sessions that are escalated to a live customer service representative
* The number of agent queries that cause a knowledge source error
What should you identify for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
Explanation:
In Microsoft Copilot Studio analytics, each metric is designed to measure a different aspect of agent performance.
For the first requirement, the metric that tracks the percentage of engaged sessions escalated to a live customer service representative is Escalation rate. This directly measures how often conversations are handed off from the agent to a human.
For the second requirement, the metric that helps identify queries causing a knowledge source error is Answer quality. This area evaluates how well the agent responds and includes issues related to grounded answers, failed responses, and knowledge-source-related problems.
Why the other options are not correct:
Customer Satisfaction (CSAT) score measures user satisfaction, not escalation percentage or knowledge source errors.
Engagement rate measures whether users actively interact with the agent, not whether sessions are escalated or whether a knowledge source failed.
問題 #96
A retail company plans to deploy Microsoft Copilot Studio agents to support:
Microsoft Dynamics 365 Commerce scenarios.
A Microsoft Power Apps inventory management solution.
You need to recommend a solution to organize product catalog data as a consistent source for multiple AI systems.
What should you recommend?
答案：C
解題說明：
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answer is D. Centralize the product catalog data in Microsoft Dataverse and expose the data to both agents.
This scenario is about creating a consistent, reusable, governed product data source for multiple AI systems across:
Dynamics 365 Commerce
a Power Apps inventory management solution
multiple Copilot Studio agents
That requirement strongly points to Microsoft Dataverse as the shared business data platform.
Why D is correct
Dataverse is the best fit because it provides:
a centralized business data store
a consistent schema for product catalog records
native integration with Power Platform
strong compatibility with Dynamics 365
governed access and reuse across multiple AI systems
From an AI business solutions perspective, a product catalog is core enterprise reference data. It should not be fragmented across agents or scraped from documents. It should exist as a single source of truth that can serve multiple applications and copilots.
By centralizing the catalog in Dataverse, the company gains:
consistency across apps and agents
easier maintenance
better governance
cleaner analytics and grounding
less duplication and drift
This is exactly the kind of design pattern used for scalable agentic business solutions.
Why the other options are incorrect
A). Let each agent scrape product details from Microsoft SharePoint Online libraries This is brittle, less structured, and not ideal for maintaining a consistent enterprise product catalog. SharePoint is not the best source of truth for structured operational catalog data.
B). Store the product catalog data in a separate custom table for each agent This creates duplication, inconsistency, and governance problems. It directly conflicts with the requirement for a consistent source across multiple AI systems.
C). Configure prompts to pull product details from the PDFs of external vendors PDFs are a weak source for central operational product master data. This would increase inconsistency and reduce reliability.
Expert reasoning
When a question asks for a shared, consistent business data source across:
Copilot Studio
Power Apps
Dynamics 365
the best answer is usually Microsoft Dataverse.
So the correct choice is:
問題 #97
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 add the opportunity summary widget to the Opportunity form. Does this meet the goal?
答案：A
解題說明：
Adding the opportunity summary widget to the Opportunity form can make the summary visible in the user interface, but it does not tailor how the summary is generated, nor does it meaningfully customize its presentation logic beyond placement.
The question asks whether this meets the goal of customizing Copilot by tailoring:
* how opportunity summaries are generated, or
* how they are presented to users
Simply placing the widget on the form is more of a UI inclusion step than a true customization of Copilot summary behavior or rendering logic.
問題 #98
What should you recommend to assist the CTO with the prebuilt agent selection process?
答案：B
解題說明：
The CTO wants to view available prebuilt agent templates in Dynamics 365 Supply Chain Management to decide which one should be prioritized for deployment. Agent management is the feature used to discover, review, and manage available agent templates and capabilities for Dynamics 365 business applications.
Why this is correct:
It supports discovering available prebuilt agents
It helps evaluate which agent can deliver the most business value
It aligns with the requirement to preview and assess candidate agents during the selection phase Why the other options are not correct:
B). Immersive Home is more of an experience surface, not the primary tool for selecting prebuilt agent templates C). Lifecycle Services (LCS) is used for environment and application lifecycle management, not for browsing Dynamics 365 AI agent templates D). Copilot Studio is primarily for building/customizing copilots and agents, not for selecting Dynamics 365 prebuilt Supply Chain Management agent templates
問題 #99
A company uses Microsoft Dynamics 365 Supply Chain Management.
You are designing an AI supply chain process that meets the following requirements:
Provides managers with AI-driven insights that surface key information from customer orders Helps planners use AI to anticipate future product needs more accurately You need to recommend which Microsoft Copilot features to include in the design.
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.
答案：
解題說明：
Explanation:
Provide AI-driven insights from customer orders # AI Summaries with Copilot; Anticipate future product needs # Generative insights for Demand planning The first requirement is to give managers AI-driven insights that surface key information from customer orders.
That aligns best with AI Summaries with Copilot, because summaries are designed to extract and present the most important information from operational records in a concise, business-friendly way. In a supply chain context, this helps managers quickly understand:
important order details
exceptions or risks
priority items
fulfillment context
notable changes or issues tied to customer orders
From an AI business solutions perspective, this is exactly the kind of feature used to reduce manual review effort and improve decision speed. Rather than reading through many order records, managers get a synthesized view of key information.
Why "Generative insights for Demand planning" is correct
The second requirement is to help planners anticipate future product needs more accurately.
This directly maps to Generative insights for Demand planning. Demand planning is the business function focused on forecasting future demand, identifying trends, and improving planning accuracy for inventory and supply decisions.
Generative insights in this area help planners by surfacing patterns, explaining forecast behavior, and supporting better forward-looking decisions about product demand.
From an agentic AI business solutions standpoint, this is the right fit because it applies AI to:
forecast interpretation
trend identification
planning support
future demand anticipation
more accurate product need estimation
Why the other options are incorrect
Workload insights with Copilot
This is not the best match for surfacing key information from customer orders. It is more associated with operational workload visibility than customer-order summarization.
Microsoft Power BI
Power BI is useful for analytics and dashboards, but the question specifically asks for a Microsoft Copilot feature to anticipate future product needs. The direct feature match is Generative insights for Demand planning.
The Customer credit and collections workspace
This is focused on finance and collections activity, not on supply chain customer-order insight summarization.
Product information management
This manages product data and attributes, not AI-driven future demand anticipation.
The Supplier Communications Agent
This is related to supplier communication workflows, not demand forecasting for future product needs.
Expert reasoning
A quick exam shortcut here is:
Surface key information from records/orders # think AI Summaries with Copilot Anticipate future demand/product needs # think Generative insights for Demand planning
問題 #100
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