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| Section | Weight | Objectives |
|---|---|---|
| Plan AI-powered business solutions | 25% | - AI solution design strategy
|
| Deploy AI-powered business solutions | 45% | - Testing and validation
|
| Design AI-powered business solutions | 30% | - Agent and solution design
|
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NEW QUESTION # 86
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.
Answer:
Explanation:
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
NEW QUESTION # 87
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: D,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 # 88
Which framework should you use for the infrastructure migration?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answer is A. Microsoft Cloud Adoption Framework for Azure .
In this scenario, Fabrikam is moving from a fully on-premises environment to a completely cloud-based topology , and the requirements explicitly state that:
* Azure must be used for all future infrastructure workloads
* the company must follow Microsoft-recommended methodologies for infrastructure migration to the cloud That wording points directly to the Microsoft Cloud Adoption Framework for Azure .
The Cloud Adoption Framework is Microsoft's primary guidance for planning and executing enterprise cloud migrations. It is not just a technical migration checklist; it is a full strategic framework that helps organizations move workloads to Azure in a structured and governed way. It covers key areas such as:
* migration strategy
* readiness assessment
* governance
* identity and security planning
* landing zones
* operations management
* organizational alignment
* adoption planning
From an AI-powered business solutions perspective, this matters because AI solutions only succeed when the underlying infrastructure is modernized correctly. Fabrikam's goals include cloud migration, Dataverse consolidation, Dynamics 365 Sales adoption, and AI-first business operations. All of these depend on a strong Azure-based cloud foundation. The Cloud Adoption Framework helps ensure that this transformation is done in a way that is scalable, secure, and aligned to business outcomes.
Why the other options are incorrect:
B). Success by Design
This framework is mainly used for designing and implementing business applications in a way that improves adoption, usability, and solution quality. It is highly relevant for conversational experiences , application rollout, and ensuring users get value from solutions such as Dynamics 365 and Copilot-related implementations. However, it is not the primary framework for infrastructure migration to Azure .
C). Microsoft Power Platform Center of Excellence (CoE)
The CoE is used to establish governance, monitoring, best practices, and enablement for Power Platform usage across an organization. It helps manage makers, apps, flows, and adoption across Power Platform environments. While it is useful after adoption begins, it is not the framework used to migrate enterprise infrastructure to Azure .
D). Microsoft Power Platform Project Setup Wizard
This is more of a project setup and configuration aid for Power Platform implementations. It does not provide enterprise-scale migration guidance for moving an organization's infrastructure from on-premises systems to Azure.
Expert reasoning:
When a question mentions infrastructure migration , Azure , and Microsoft-recommended methodology , the best match is almost always the Microsoft Cloud Adoption Framework for Azure . In Microsoft solution architecture and AI business transformation scenarios, this framework is the standard answer for cloud migration planning and execution.
Topic 1, Fabrikam, Inc
Background - Fabrikam, Inc., is a global consumer goods company that is undergoing a digital transformation initiative to migrate its entire infrastructure to the Microsoft cloud. As a key element of this cloud migration, the company will implement Microsoft Dynamics 365 Sales, moving away from the current on-premises proprietary technologies used by its business-to-business (B2B) sales team. As part of the cloud migration, Fabrikam will adopt an AI-first approach to its business solutions and implement AI solutions, wherever possible, to streamline operations. Problem Statements - Fabrikam ' s infrastructure currently relies on various on-premises systems that require sales executives to use corporate computers with physical keyboards to access business information during customer interactions. Mobile phones cannot be used for these purposes, as the systems depend on keyboard input. As a result, the sales executives spend a lot of time using keyboards to search for data on several disparate systems and file servers, rather than focusing on the customers. This affects the customer experience. Fabrikam stakeholders are concerned that users will be hesitant to adopt AI. If the AI initiatives are NOT adopted, cost savings will never be realized. Additionally, funding for future AI initiatives will depend on demonstrating an increase in AI adoption month over month.
As the AI agent initiative for the sales team will be the first for Fabrikam, the rapid adoption of the agent is a high priority. Planned Initiatives - General - Fabrikam management has prioritized AI-driven projects to improve efficiency, customer engagement, and responsible AI adoption. The current application infrastructure is on-premises and must be migrated to the cloud to support the adoption of these technologies. Infrastructure Migration - Fabrikam plans to migrate from its current on-premises infrastructure to a completely cloud-based topology; this will include user authentication, the security framework, and, primarily, the adoption of the services by end users. All the data from the different systems will be consolidated into a single data source - a common data model that will use a Microsoft Dataverse environment as a single source of truth (SSOT) for the sales team. Sales Cycle Enablement - To achieve the company ' s objectives, Fabrikam intends to implement the following strategies to enhance the sales cycle: Use low-code development to create a single AI agent that has Dataverse as its core component. Ensure that sales managers can access unanswered correspondence from prospects and intervene as appropriate. Replace the previous proprietary software with Dynamics 365 Sales to track sales cycles and customer interactions. Have the sales executives use Dynamics
365 Sales to track interactions for open opportunities and send follow-up communications to prospects. Have the sales executives use handsfree headsets to interact with an AI agent when they have questions about internal policies or customer data. Requirements - Infrastructure Migration - Fabrikam has identified the following infrastructure migration requirements: Azure must be used for all future infrastructure workloads.
The company must follow Microsoft-recommended methodologies for infrastructure migration to the cloud.
Any created AI agents must have their return on investment (ROI) calculated to ensure that the solution will save the company money. Sales Cycle Enablement - Fabrikam has identified the following requirements for sales cycle enablement: The final AI agent must follow Microsoft recommendations for a conversational user experience. A designated checklist must be reviewed to ensure that the AI agent follows Microsoft deployment recommendations for a compliant solution. Detailed telemetry must be logged for the first created AI agent to help troubleshoot and optimize the agent during the initial AI agent adoption process. Unexpected AI agent actions must end in an escalation to a live representative. For example, a sales executive must be rerouted to a representative if the agent cannot answer a question after two failed attempts. The return on investment (ROI) of switching from the current process to the future process is required for stakeholder sign off. The sales team must use Dynamics 365 Sales to correspond with prospects more quickly and efficiently than currently. Sales managers must report on the adoption of the AI agent to key Fabrikam stakeholders on a monthly basis. Any sensitive information, such as user IDs and names, shared via the AI agent must be tracked for future auditing.
NEW QUESTION # 89
A company has a Microsoft Copilot Studio agent that uses custom connectors to interact with enterprise APIs.
You need to recommend an application lifecycle management (ALM) process to ensure that the connectors are deployed consistently across development, test, and production environments and meet governance and traceability requirements.
What should you recommend?
Answer: C
Explanation:
To implement a robust Application Lifecycle Management (ALM) process for Microsoft Copilot Studio agents using custom connectors, you must leverage Solutions and Environment Variables to ensure consistency and governance.
1. Solution-Based Management
Always develop your custom connectors and Copilot Studio agents within a Power Platform Solution. This allows you to package all related components (connectors, environment variables, and agents) as a single unit for deployment across your ALM pipeline (Dev → Test → Prod).
2. Implementing Environment Variables
To maintain consistent definitions and meet governance requirements, externalize environment- specific values using Environment Variables:
Host and Base URL: Use environment variables for the API endpoint (e.g., api.dev.enterprise.com vs. api.prod.enterprise.com) to avoid manual edits during deployment.
Security Credentials: For OAuth settings like Client ID and Client Secret, use environment variables with the Secret data type.
Azure Key Vault Integration: For high-security enterprise APIs, store secrets in Azure Key Vault and reference them via secret environment variables to ensure traceability and governance.
Reference:
https://learn.microsoft.com/en-us/copilot/finance/get-started/custom%20connectors/custom- connectors-solutions
NEW QUESTION # 90
A company has a portfolio of AI initiatives at different stages of development.
You need to recommend a structured approach to evaluating the return on AI investment (ROAI) across all the initiatives. The solution must balance immediate results with long-term values and strategic innovations.
What should you include in the recommendation?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Agentic AI Business Solutions Topics:
The correct answer is B. a horizon-based framework.
This question is about evaluating ROAI across a portfolio of AI initiatives that are at different stages of development. The key requirement is to use a structured approach that balances:
immediate results
long-term value
strategic innovation
That wording maps directly to a horizon-based framework.
Why B is correct
A horizon-based framework is designed to evaluate investments across different time horizons, typically separating initiatives into categories such as:
near-term / operational value
mid-term / growth and optimization value
long-term / transformational or strategic innovation value
This makes it ideal for AI portfolios, because AI initiatives rarely create value on the same timeline.
For example:
one AI initiative may reduce support costs this quarter
another may improve forecasting over the next year
another may be experimental but create major strategic advantage later
A horizon-based framework helps leadership avoid a common mistake in AI investment governance: judging every initiative only by short-term ROI.
From an agentic AI business solutions perspective, this is especially important because AI portfolios often include a mix of:
automation projects
copilots and agents
analytics and prediction models
innovation pilots
foundational data and governance investments
Some of these generate measurable savings quickly, while others create value through capability-building, competitive advantage, or future scalability. A horizon-based framework gives a balanced and executive- friendly way to assess all of them.
Why the other options are incorrect
A). a simple cost and benefit analysis
This is too narrow for a portfolio of AI initiatives with different maturity levels. It may help with individual projects, but it does not effectively balance short-term wins with longer-term innovation value.
C). the internal rate of return (IRR) function
IRR is a financial evaluation tool, but it is not the best structured portfolio framework for AI initiatives, especially where strategic and non-immediate benefits matter. AI value often includes intangible and capability-based outcomes that IRR alone does not capture well.
D). a prioritization grid
A prioritization grid helps rank initiatives, usually by factors like impact and effort, but it is not primarily a framework for evaluating ROAI over different time horizons. It supports selection, not full portfolio return evaluation.
Expert reasoning
When a question includes these ideas together:
portfolio of initiatives
different stages of development
immediate and long-term value
strategic innovation
the strongest answer is a horizon-based framework.
That is the best way to assess AI investments across short-term, medium-term, and transformational horizons without undervaluing strategic initiatives.
NEW QUESTION # 91
......
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