Microsoft Agentic AI Business Solutions Architect AB-100 Exam Questions in PDF

Free Microsoft AB-100 Dumps Questions (page: 1)


Case study

This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam time as you would like to complete each case study. However, there might be additional case studies or other exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections that follow this case study.

To answer the case study questions, you will need to reference information that is provided in the case. Case studies and associated questions might contain exhibits or other resources that provide more information about the scenario described in the case. Information provided in an individual question does not apply to the other questions in the case study.

A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change your answers before you move to the next exam section. After you leave this case study, you will NOT be able to return to it.

To start the case study

To display the first question in this case study, select the "Next" button. To the left of the question, a menu provides links to information such as business requirements, the existing environment, and problem statements. Please read through all this information before answering any questions. When you are ready to answer a question, select the "Question" button to return to the question.

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.

Which two components in the custom AI agent design should the CFO evaluate in the quarterly agent analysis? Each correct answer presents part of the solution.

Note: Each correct selection is worth one point.

  1. the GPT models used for the agent
  2. the average characters in a chat message
  3. the agent orchestration method
  4. the average session time per agent

Answer(s): C,D

Explanation:

Scenario:
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.
--
Quarterly Estimated ROI (Forecasting)
Use the Microsoft Agent Usage Estimator to model quarterly expectations before each period.
Orchestration Method Input: Select between Classic (logic-driven) or Generative (AI-driven) orchestration.
Generative orchestration typically consumes more credits but reduces manual development time.
Session Time Variables: Model the average session time per agent to estimate total message volume. The estimator uses this to project credit consumption based on interaction depth.
Target ROI Formula: Define the benchmark as:
Estimated Savings = (Projected Deflection × Human Agent Cost) - Estimated Credit Cost.


Reference:

https://alrafayglobal.com/measure-your-ai-chatbot-roi-copilot-studio




Case study

This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam time as you would like to complete each case study. However, there might be additional case studies or other exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections that follow this case study.

To answer the case study questions, you will need to reference information that is provided in the case. Case studies and associated questions might contain exhibits or other resources that provide more information about the scenario described in the case. Information provided in an individual question does not apply to the other questions in the case study.

A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change your answers before you move to the next exam section. After you leave this case study, you will NOT be able to return to it.

To start the case study

To display the first question in this case study, select the "Next" button. To the left of the question, a menu provides links to information such as business requirements, the existing environment, and problem statements. Please read through all this information before answering any questions. When you are ready to answer a question, select the "Question" button to return to the question.

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 configure for the custom AI agent?

  1. AI-assisted evaluators
  2. classic orchestration
  3. generative orchestration
  4. Azure OpenAI reasoning models

Answer(s): C

Explanation:

Generative orchestration is the most appropriate choice for this Microsoft Dynamics 365 AI agent solution.
This selection directly addresses your requirements for a low-code, conversational, and interconnected agent ecosystem within the Microsoft Power Platform and Dynamics 365 environment.
Why Generative Orchestration?
Generative orchestration (available in Microsoft Copilot Studio) is specifically designed to move away from rigid, trigger-phrase-based logic toward a flexible, intent-based model.
Mapping to Your Requirements
Intent-Based Selection: Unlike "Classic" orchestration which relies on exact trigger phrases, generative orchestration uses Natural Language Understanding (NLU). It selects the correct topic or "sub-agent" based on a description of the purpose, allowing for the conversational flow you requested.
Low-Code Integration: Copilot Studio is the primary low-code tool for Dynamics 365. It provides native connectors to Supply Chain Management (SCM) data and can be embedded directly into the SCM interface or deployed to Microsoft Teams.
External Business Logic: It can trigger Power Automate flows or API calls to execute business logic stored in external databases or legacy systems, bringing that data back into the conversation.
Product Specifications: By using Generative Answers, the agent can crawl "existing technologies" like SharePoint libraries, internal wikis, or SCM data tables to answer complex spec questions without manual topic authoring.

Incorrect:
[Not A]
AI-Assisted Evaluators are testing and diagnostic tools, not runtime execution engines.
You would use these to measure how well your agent is performing, but they cannot be the agent or manage the logic flow.
[Not B]
Classic Orchestration is entirely dependent on trigger phrases.
It creates a "command-and-control" feel rather than the fluid, conversational interaction you are looking for. It also scales poorly when trying to connect multiple agents.
[Not D]
Azure OpenAI Models (Reasoning Models) while powerful, this is a pro-code path (API-heavy).
Using raw Azure OpenAI models would require significant custom development, missing the "low-code" requirement. While Generative Orchestration uses these models under the hood, the orchestration layer itself is what manages the "which agent to call" logic.
Scenario: 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.


Reference:

https://www.syncfusion.com/blogs/post/integrating-ai-into-your-apps-with-ai-builder




Case study

This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam time as you would like to complete each case study. However, there might be additional case studies or other exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case studies and associated questions might contain exhibits or other resources that provide more information about the scenario described in the case. Information provided in an individual question does not apply to the other questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change your answers before you move to the next exam section. After you leave this case study, you will NOT be able to return to it.

To start the case study

To display the first question in this case study, select the "Next" button. To the left of the question, a menu provides links to information such as business requirements, the existing environment, and problem statements. Please read through all this information before answering any questions. When you are ready to answer a question, select the "Question" button to return to the question.
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.

HOTSPOT

Which framework should you use to meet the AI agent requirements for the sales cycle enablement? To answer, select the appropriate options in the answer area.

Note: Each correct selection is worth one point.

Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box 1: the ALM Accelerator for Microsoft Power Platform
For Microsoft Copilot Studio best practices

Using the ALM Accelerator for Microsoft Power Platform is a recommended approach for managing the lifecycle of a low-code AI agent (Copilot Studio) that relies on Dataverse. It enables source control, versioning, and automated deployment of AI agents to ensure they follow Microsoft's best practices.

Box 2: Microsoft Power Platform Well-Architected framework
For conversational user experience

Utilizing the Microsoft Power Platform Well-Architected framework for a low-code AI agent (built in Copilot Studio) with Dataverse as the core data component ensures the solution is secure, reliable, and provides a high-quality conversational user experience (CUX). The framework helps align the agent with Microsoft's best practices for responsible AI, efficiency, and user satisfaction.

Scenario:
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.

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.




Case study

This is a case study. Case studies are not timed separately from other exam sections. You can use as much exam time as you would like to complete each case study. However, there might be additional case studies or other exam sections. Manage your time to ensure that you can complete all the exam sections in the time provided. Pay attention to the Exam Progress at the top of the screen so you have sufficient time to complete any exam sections that follow this case study.
To answer the case study questions, you will need to reference information that is provided in the case. Case studies and associated questions might contain exhibits or other resources that provide more information about the scenario described in the case. Information provided in an individual question does not apply to the other questions in the case study.
A Review Screen will appear at the end of this case study. From the Review Screen, you can review and change your answers before you move to the next exam section. After you leave this case study, you will NOT be able to return to it.

To start the case study

To display the first question in this case study, select the "Next" button. To the left of the question, a menu provides links to information such as business requirements, the existing environment, and problem statements. Please read through all this information before answering any questions. When you are ready to answer a question, select the "Question" button to return to the question.
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.

Which framework should you use for the infrastructure migration?

  1. Microsoft Cloud Adoption Framework for Azure
  2. Success by Design
  3. Microsoft Power Platform Center of Excellence (CoE)
  4. Microsoft Power Platform Project Setup Wizard

Answer(s): A

Explanation:

For migrating a legacy on-premises infrastructure to Microsoft Dynamics 365 Sales with Dataverse as the Single Source of Truth (SSOT), the recommended framework is the Microsoft Cloud Adoption Framework for Azure (CAF), specifically utilized in conjunction with the Data Management Framework (DMF) for Dynamics 365.
This combined approach ensures a structured transition by focusing on both the strategic adoption of cloud technology and the technical, granular migration of data.
Recommended Framework: Microsoft Cloud Adoption Framework (CAF) The CAF provides a holistic structure to ensure the migration is secure, compliant, and aligned with business goals.
Plan: Assess legacy data, prioritize workloads, and define the SSOT requirements.
Ready: Set up the Dataverse environment (landing zone) and configure security (Azure Active Directory/ Microsoft Entra ID).
Adopt (Migrate): Perform the technical migration of data using ETL (Extract, Transform, Load) processes.
Scenario:
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.
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.



A company uses Microsoft Dynamics 365 Sales to manage leads that are stored in a Microsoft Dataverse table named Lead and use non-standard terminology and custom columns.

You need to configure business terms in the Lead table so that Microsoft Copilot controls can summarize the leads efficiently. The solution must minimize administrative effort.

How should you configure the business terms?

  1. Combine all the fields into one custom field.
  2. Map the field display names as business terms.
  3. Add the schema names as business terms.
  4. Create new business terms for each field.

Answer(s): B

Explanation:

To configure Microsoft Copilot to efficiently summarize leads with non-standard terminology and custom columns in Microsoft Dynamics 365 Sales, you must map these unique fields to business terms within the Sales AI Glossary in Microsoft Copilot Studio.
Note:
To map your field display names as business terms:
1. Access Copilot Studio: Open Microsoft Copilot Studio and select the environment containing your Dynamics 365 Sales instance.
2. Select the Sales Agent: Navigate to Agents and select the agent named Copilot in Dynamics 365 Sales (formerly Sales Copilot Power Virtual Agents Bot).
3. Navigate to Knowledge: Under the Knowledge section, select the SalesSpecificQnA knowledge source.
4. Add Glossary Entries:
Go to the Glossary tab.
Term: Enter the non-standard or custom field display name (e.g., your custom business term).
Description: Define how this term relates to the Dataverse schema. This helps Copilot understand the logic behind the custom column.
5. Configure Synonyms: In the Synonyms section, map your custom field to alternative names that sellers might use in natural language queries (e.g., mapping "Custom Revenue" to "Opportunity Revenue").
6. Publish Changes: Select Publish to apply these mappings, allowing Copilot to use the newly defined terms when generating lead summaries.



DRAG DROP (Drag and Drop is not supported)

You are designing two Microsoft Copilot Studio agents named Agent1 and Agent2. Each agent must meet the following requirements:

Each agent must use a standard model.

Each agent must NOT use generative orchestration.

Agent1 must support simple and short phrases for a given topic.

Agent2 must integrate with Microsoft Dynamics 365 Contact Center voice channel.

You need to recommend language models for the agents.

What should you recommend for each agent? To answer, drag the appropriate language models to the correct agents. Each language model 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.

Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box 1: Natural Language Understanding (NLU)
Agent1 must support simple and short phrases for a given topic.

For a Microsoft Copilot Studio agent that must not use generative orchestration and requires support for simple, short trigger phrases, the best choice is the Classic NLU (Natural Language Understanding) model.

When you disable generative orchestration (also known as "Generative mode" or "Generative AI" orchestration), the agent reverts to Classic orchestration. In this mode, the agent relies on predefined trigger phrases to map user input directly to specific topics.

Box 2: Natural Language Understanding + (NLU +)
Agent2 must integrate with Microsoft Dynamics 365 Contact Center voice channel.

For a Microsoft Copilot Studio agent using classic orchestration (no generative orchestration) and integrating with the Dynamics 365 Contact Center voice channel, the best language model is NLU+.

Why NLU+ is the Best Choice
While standard agents offer three "classic" Natural Language Understanding (NLU) options, NLU+ is specifically designed for high-performance, enterprise-grade scenarios like voice channels.

Note:
Comparison of Classic Models



A company uses Microsoft Dynamics 365 finance and operations apps.

The company plans to use Microsoft Copilot in-app help and guidance to generate responses for internal business processes.

You need to add an additional knowledge source for the business processes. The solution must NOT add new topics to the Copilot agent for the finance and operations apps.

Which knowledge source should you add?

  1. Microsoft Dataverse
  2. a public website
  3. Azure AI Search
  4. a file upload

Answer(s): D

Explanation:

To add an additional knowledge source for internal business processes to the Microsoft Copilot in-app experience for Dynamics 365 finance and operations apps--without creating new topics--you should add File Uploads (such as PDF, Word, or text documents) to the "Copilot for finance and operations apps" agent in Copilot Studio.



A company has an AI business solution.

You need to extend the solution so that Microsoft 365 Copilot can invoke external logic hosted in Azure services.

What should you include in the solution?

  1. Microsoft Copilot Studio skills
  2. Microsoft Power Platform connectors
  3. custom engine agents

Answer(s): B

Explanation:

To enhance an AI business solution with Microsoft 365 Copilot and integrate external logic hosted in Azure, you should use Copilot Studio to create Actions. These actions act as plugins that allow Copilot to invoke external services through Power Platform components.
Implementation Strategy
Azure Logic Hosting: Host your external logic in Azure using services like Azure Functions or Azure Logic Apps. These provide the API endpoints that Copilot will ultimately call.
*-> Power Platform Connector: Create a Custom Connector in the Power Platform to wrap your Azure service's API. This connector acts as the bridge, translating Copilot's requests into API calls your Azure logic understands.
Copilot Studio Integration: Within Microsoft Copilot Studio, add the custom connector as a Tool or Action. This makes the logic discoverable and invokable by Microsoft 365 Copilot.
Deployment: Deploy the action through the Microsoft 365 admin center under Integrated Apps to make it available to users in Teams or other Microsoft 365 apps.
Key Components
*-> Connector: Wraps the Azure API using an OpenAPI definition or Postman collection.
Plugin/Action: Defines how Copilot identifies when to use the connector based on user prompts.
Authentication: Ensure the connector is configured with appropriate security (e.g., OAuth 2.0) to safely access your Azure resources.



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T
Tom
3/18/2022 8:00:00 PM

i purchased this exam dumps from another website with way more questions but they were all invalid and outdate. this exam dumps was right to the point and all from recent exam. it was a hard pass.

E
Edrick GOP
10/24/2023 6:00:00 AM

it was a good experience and i got 90% in the 200-901 exam.

A
anonymous
8/10/2023 2:28:00 AM

hi please upload this

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Bakir
7/6/2023 7:24:00 AM

please upload it

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Aman
6/18/2023 1:27:00 PM

really need this dump. can you please help.

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Neela Para
1/8/2024 6:39:00 PM

really good and covers many areas explaining the answer.

K
Karan Patel
8/15/2023 12:51:00 AM

yes, can you please upload the exam?

N
NISHAD
11/7/2023 11:28:00 AM

how many questions are there in these dumps?

P
Pankaj
7/3/2023 3:57:00 AM

hi team, please upload this , i need it.

D
DN
9/4/2023 11:19:00 PM

question 14 - run terraform import: this is the recommended best practice for bringing manually created or destroyed resources under terraform management. you use terraform import to associate an existing resource with a terraform resource configuration. this ensures that terraform is aware of the resource, and you can subsequently manage it with terraform.

Z
Zhiguang
8/19/2023 11:37:00 PM

please upload dump. thanks in advance.

D
deedee
12/23/2023 5:51:00 PM

great great

A
Asad Khan
11/1/2023 3:10:00 AM

answer 16 should be b your organizational policies require you to use virtual machines directly

S
Sale Danasabe
10/24/2023 5:21:00 PM

the question are kind of tricky of you didnt get the hnag on it.

L
Luis
11/16/2023 1:39:00 PM

can anyone tell me if this is for rhel8 or rhel9?

H
hik
1/19/2024 1:47:00 PM

good content

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Blessious Phiri
8/15/2023 2:18:00 PM

pdb and cdb are critical to the database

Z
Zuned
10/22/2023 4:39:00 AM

till 104 questions are free, lets see how it helps me in my exam today.

M
Muhammad Rawish Siddiqui
12/3/2023 12:11:00 PM

question # 56, answer is true not false.

A
Amaresh Vashishtha
8/27/2023 1:33:00 AM

i would be requiring dumps to prepare for certification exam

A
Asad
9/8/2023 1:01:00 AM

very helpful

B
Blessious Phiri
8/13/2023 3:10:00 PM

control file is the heart of rman backup

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Senthil
9/19/2023 5:47:00 AM

hi could you please upload the ibm c2090-543 dumps

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Harry
6/27/2023 7:20:00 AM

appriciate if you could upload this again

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Anonymous
7/10/2023 4:10:00 AM

please upload the dump

R
Raja
6/20/2023 5:30:00 AM

i found some questions answers mismatch with explanation answers. please properly update

D
Doora
11/30/2023 4:20:00 AM

nothing to mention

D
deally
1/19/2024 3:41:00 PM

knowable questions

S
Sonia
7/23/2023 4:03:00 PM

very helpfull

B
binEY
10/6/2023 5:15:00 AM

good questions

N
Neha
9/28/2023 1:58:00 PM

its helpful

D
Desmond
1/5/2023 9:11:00 PM

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D
Davidson OZ
9/9/2023 6:37:00 PM

22. if you need to make sure that one computer in your hot-spot network can access the internet without hot-spot authentication, which menu allows you to do this? answer is ip binding and not wall garden. wall garden allows specified websites to be accessed with users authentication to the hotspot

3
381
9/2/2023 4:31:00 PM

is question 1 correct?

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