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| Section | Weight | Objectives |
|---|---|---|
| Plan AI-powered business solutions | 25โ30% | - Evaluate costs and benefits
|
| Deploy AI-powered business solutions | 40โ45% | - Manage testing and validation
|
| Design AI-powered business solutions | 25โ30% | - Design extensibility and integration
|
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NEW QUESTION # 89
A company extends Copilot in Microsoft Dynamics 365 Customer Service.
You need to recommend an automated application lifecycle management (ALM) process so that the Copilot components can be safely developed, tested, and promoted to production.
Which two actions should you include in the ALM process? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: C,E
Explanation:
To implement an automated Application Lifecycle Management (ALM) process for extending Microsoft Dynamics 365 Customer Service with Copilot, you should leverage Power Platform solutions and pipelines. This approach ensures that custom agents, knowledge sources, and connector actions are developed and promoted safely across environments.
Tools used include:
Power Platform Pipelines: Automates the deployment process across environments.
To automate the application lifecycle management (ALM) for Copilot components within Microsoft Dynamics 365 Customer Service, follow this structured process using Power Platform pipelines and solutions:
1. Solution-Centric Development
All Copilot components (agents, topics, custom actions, and connector plugins) must be developed within a Power Platform solution.
Create or Select a Solution: In Copilot Studio or the Power Apps maker portal, ensure you are working within an unmanaged solution in your Development environment.
Add Components: When you create new agents or actions in Microsoft Copilot Studio, they are automatically associated with the preferred solution you have set, ensuring they are portable.
2. Pipeline Configuration
Power Platform pipelines democratize ALM by providing a built-in CI/CD experience directly within the maker portal.
Reference:
https://intelequia.com/en/blog/post/maximize-the-value-of-power-platform-with-effective-alm-and- the-power-of-ai
https://learn.microsoft.com/en-us/power-platform/release-plan/2024wave2/microsoft-copilot- studio/solution-management-copilot-studio
NEW QUESTION # 90
You need to design a Microsoft 365 Copilot solution to optimize employee productivity. The solution must meet the following requirements:
- Ensure that the employees can query content stored in a subset of
Microsoft SharePoint Online sites and in Teams by using natural
language-based prompt actions.
- Ensure that employees receive contextually relevant responses in
Microsoft 365 Copilot.
What should you include in the design?
Answer: C
Explanation:
To enable Microsoft 365 Copilot to query a specific subset of SharePoint Online and Teams content using natural language, you can implement a combination of Restricted SharePoint Search and Microsoft Graph Connectors.
1. Restricting Content Access
You can limit the scope of data Copilot searches by using features that control which sites are indexed or accessible.
2. Configuring Microsoft Graph Access
Microsoft Graph acts as the bridge connecting Copilot to your organizational data. To integrate specific sources.
3. Enabling Prompt Actions & Context
Declarative Agents: You can create specialized Copilot Agents grounded in specific SharePoint knowledge sources. These agents use natural language instructions to focus on a subset of data for more contextually relevant responses.
Direct Referencing: Users can improve response relevance by explicitly naming files, folders, or Teams channels in their natural language prompts (e.g., "Summarize notes from the 'Product Launch' channel").
Reference:
https://nboldapp.com/advanced-microsoft-365-copilot-techniques-prompting-grounding-and- automation/
NEW QUESTION # 91
You are evaluating a Microsoft Copilot Studio agent that supports Microsoft Dynamics 365 Customer Service representatives.
You need to recommend a testing solution that meets the following requirements:
Evaluates agent effectiveness during active sessions
Validates whether the agent delivers accurate and helpful responses
Provides measurable, actionable insights for continuous improvement
What should you recommend?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answer is A. Track resolution, deflection, and accuracy by using dashboards and use scripts to ensure consistent responses .
This question is about evaluating a Copilot Studio agent in live support operations , not just testing technical uptime or infrastructure performance. The requirements emphasize three things:
* effectiveness during active sessions
* response accuracy and helpfulness
* measurable insights for continuous improvement
That combination points to operational quality metrics and analytics dashboards.
Why A is correct
Tracking resolution , deflection , and accuracy directly measures how well the agent performs in real support conversations:
* Resolution shows whether the issue is successfully handled
* Deflection shows whether the agent reduces human workload appropriately
* Accuracy shows whether responses are correct and helpful
Using dashboards gives leaders and support teams measurable, ongoing visibility into agent behavior. Adding scripts for consistent testing further supports repeatable evaluation and improvement.
From an AI business solutions perspective, this is the right recommendation because it combines:
* business outcome measurement
* quality validation
* operational analytics
* continuous improvement feedback loops
This is exactly how enterprise copilots should be managed after deployment.
Why the other options are incorrect
B). Perform load testing to validate how the agent scales under a high chat volume Load testing is useful for scalability and capacity planning, but it does not directly validate whether responses are accurate, helpful, or effective during active sessions from a business-outcome perspective.
C). Review historical tickets to find agents that have the shortest resolution times This may give some retrospective insight, but it does not directly evaluate the Copilot Studio agent during active sessions, and shortest resolution time alone does not prove response quality or helpfulness.
D). Measure uptime and page load times
These are infrastructure and availability metrics. They are important for system health, but they do not evaluate conversational effectiveness or answer quality.
Expert reasoning
For Copilot evaluation questions:
* if the goal is business effectiveness in active sessions , use resolution/deflection/accuracy
* if the goal is system scale , use load testing
* if the goal is infrastructure reliability , use uptime and latency
NEW QUESTION # 92
Drag and Drop Question
A company has a cloud-based Al solution that uses Azure OpenAI models.
You need to design a monitoring solution that meets the following requirements:
- Monitors performance metrics and operational health for the models
- Monitors Al apps and agents for compliance
- Uses Azure-native capabilities
- Minimizes development effort
What should you use for each requirement? To answer, drag the appropriate options to the correct requirements. Each option 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 # 93
A company has an Al solution named Solution1 that is deployed to the production environment.
Solution! 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 Al principles.
What should you recommend?
Answer: B
Explanation:
The scenario describes a deployed AI solution using Azure OpenAI that exhibits bias (creating disparate outcomes based on customer traits). This directly impacts the Fairness principle of Microsoft's Responsible AI framework.
Why "Modify the system instructions" is the Correct Strategy:
Direct Control via System Metaprompts: In large language model (LLM) applications like those powered by Azure OpenAI, the system instructions (or system message) define the behavior, constraints, and tone of the model. By modifying these instructions, you can explicitly direct the model to treat all customer segments equitably and ignore specific sensitive traits when drafting marketing content.
NEW QUESTION # 94
......
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