In order to set realistic expectations, please note: These questions are NOT official questions that you will find on the official exam. These questions DO cover all the material outlined in the knowledge sections below. Many of the questions are based on fictitious scenarios which have questions posed within them.

The official knowledge requirements for the exam are reviewed routinely to ensure that the content has the latest requirements incorporated in the practice questions. Updates to content are often made without prior notification and are subject to change at any time.

Each question has a detailed explanation and links to reference materials to support the answers which ensures accuracy of the problem solutions.

The questions will be shuffled each time you repeat the tests so you will need to know why an answer is correct, not just that the correct answer was item "B"  last time you went through the test.

NOTE: This course should not be your only study material to prepare for the official exam. These practice tests are meant to supplement topic study material.

Should you encounter content which needs attention, please send a message with a screenshot of the content that needs attention and I will be reviewed promptly. Providing the test and question number do not identify questions as the questions rotate each time they are run. The question numbers are different for everyone.

As a candidate for this exam, you’re an accomplished solution architect with expertise in designing and delivering AI-driven business solutions that transform business processes and foster innovation. You’re experienced in creating scalable, secure, and integrated solutions that use multiple Microsoft services to address complex organizational challenges.

Your competencies include:

• Expertise in architecting solutions that use AI, including generative AI and various AI services tailored to meet business objectives.

• The ability to design agentic-first solutions.

• Skills in designing multi-agent orchestrated solutions.

• Experience designing secure and scalable cross-platform AI solutions.

• Comprehensive knowledge of core Dynamics 365 products, Microsoft Power Platform, Microsoft Copilot Studio, Azure AI services, and Azure OpenAI.

• Proficiency in working with agents created by using Copilot Studio, AI prompts, Azure AI Foundry, and working knowledge of multiple language models to create intelligent solutions.

• Proficiency in adopting frameworks and delivering measurable outcomes aligned with enterprise success metrics and architecture patterns.

• Expertise in working with open standards and protocols, including Agent2Agent (A2A) and Model Context Protocol (MCP).

• Expertise in responsible AI practices, helping to ensure compliance and advocating for the Microsoft responsible AI guidelines.

• Strong leadership in orchestrating AI features in Microsoft business applications to optimize operations and unlock growth opportunities.

• Skills in securing AI models and data workflows, including detecting and resolving vulnerabilities, enforcing data residency and access controls, safeguarding model tuning, tracking changes, maintaining audit trails, and defending against prompt manipulation.

• Experience in monitoring agent performance and interpreting telemetry data to help ensure reliability, optimize behavior, and drive continuous improvement.

• Ability to conduct a return-on-investment (ROI) analysis of an AI-powered solution.

Expertise in architecting solutions that use AI, including generative AI and various AI services tailored to meet business objectives.

The ability to design agentic-first solutions.

Skills in designing multi-agent orchestrated solutions.

Experience designing secure and scalable cross-platform AI solutions.

Comprehensive knowledge of core Dynamics 365 products, Microsoft Power Platform, Microsoft Copilot Studio, Azure AI services, and Azure OpenAI.

Proficiency in working with agents created by using Copilot Studio, AI prompts, Azure AI Foundry, and working knowledge of multiple language models to create intelligent solutions.

Proficiency in adopting frameworks and delivering measurable outcomes aligned with enterprise success metrics and architecture patterns.

Expertise in working with open standards and protocols, including Agent2Agent (A2A) and Model Context Protocol (MCP).

Expertise in responsible AI practices, helping to ensure compliance and advocating for the Microsoft responsible AI guidelines.

Strong leadership in orchestrating AI features in Microsoft business applications to optimize operations and unlock growth opportunities.

Skills in securing AI models and data workflows, including detecting and resolving vulnerabilities, enforcing data residency and access controls, safeguarding model tuning, tracking changes, maintaining audit trails, and defending against prompt manipulation.

Experience in monitoring agent performance and interpreting telemetry data to help ensure reliability, optimize behavior, and drive continuous improvement.

Ability to conduct a return-on-investment (ROI) analysis of an AI-powered solution.

Your key responsibilities include:

• Envisioning and defining architecture strategies to integrate AI and agents into business solutions.

• Defining the roadmap for agentic-first business processes.

• Analyzing and interpreting business and technical requirements to architect comprehensive solutions.

• Designing and prototyping AI components and showcasing transformative capabilities.

• Guiding the end-to-end implementation of AI-centric solutions, helping to ensure security, scalability, and alignment with organizational goals.

• Promoting and championing the adoption of AI technologies in the development lifecycle and across business units.

• Creating a cohesive application lifecycle management (ALM) strategy for agentic-first solutions.

• Creating a cohesive environment strategy for AI-powered solutions, with consideration for third-party AI solutions.

• Guiding organizations on their way to becoming AI-forward companies.

Envisioning and defining architecture strategies to integrate AI and agents into business solutions.

Defining the roadmap for agentic-first business processes.

Analyzing and interpreting business and technical requirements to architect comprehensive solutions.

Designing and prototyping AI components and showcasing transformative capabilities.

Guiding the end-to-end implementation of AI-centric solutions, helping to ensure security, scalability, and alignment with organizational goals.

Promoting and championing the adoption of AI technologies in the development lifecycle and across business units.

Creating a cohesive application lifecycle management (ALM) strategy for agentic-first solutions.

Creating a cohesive environment strategy for AI-powered solutions, with consideration for third-party AI solutions.

Guiding organizations on their way to becoming AI-forward companies.

As an AI-first solution architect, you lead the transformation of enterprise operations by envisioning and implementing AI-powered architecture. With a focus on making the most of the full spectrum of Microsoft AI apps and services, along with business application tools, you drive innovation and help to ensure the delivery of impactful AI-powered solutions.

Skills at a glance

• Plan AI-powered business solutions (25–30%)

• Design AI-powered business solutions (25–30%)

• Deploy AI-powered business solutions (40–45%)

Plan AI-powered business solutions (25–30%)

Design AI-powered business solutions (25–30%)

Deploy AI-powered business solutions (40–45%)

Plan AI-powered business solutions (25–30%)

Analyze requirements for AI-powered business solutions

• Assess the use of agents in task automation, data analytics, and decision-making

• Review data for grounding, including accuracy, relevance, timeliness, cleanliness, and availability

• Organize business solution data to be available for other AI systems

Assess the use of agents in task automation, data analytics, and decision-making

Review data for grounding, including accuracy, relevance, timeliness, cleanliness, and availability

Organize business solution data to be available for other AI systems

Design overall AI strategy for business solutions

• Implement the AI adoption process from the Cloud Adoption Framework for Azure

• Design the strategy for building AI and agents in business solutions

• Design a multi-agent solution by using platforms such as Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry

• Develop the use cases for prebuilt agents in the solution

• Define the solution rules and constraints when building AI components with Copilot Studio, Azure AI services, and Azure AI Foundry

• Determine the use of generative AI and knowledge sources in agents built with Copilot Studio

• Determine when to build custom agents or extend Microsoft 365 Copilot

• Determine when custom AI models should be created

• Provide guidelines for creating a prompt library

• Develop the use cases for customized small language models for the solution

• Provide prompt engineering guidelines and techniques for AI-powered business solutions

• Include the elements of the Microsoft AI Center of Excellence

• Design AI solutions that use multiple Dynamics 365 apps

Implement the AI adoption process from the Cloud Adoption Framework for Azure

Design the strategy for building AI and agents in business solutions

Design a multi-agent solution by using platforms such as Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry

Develop the use cases for prebuilt agents in the solution

Define the solution rules and constraints when building AI components with Copilot Studio, Azure AI services, and Azure AI Foundry

Determine the use of generative AI and knowledge sources in agents built with Copilot Studio

Determine when to build custom agents or extend Microsoft 365 Copilot

Determine when custom AI models should be created

Provide guidelines for creating a prompt library

Develop the use cases for customized small language models for the solution

Provide prompt engineering guidelines and techniques for AI-powered business solutions

Include the elements of the Microsoft AI Center of Excellence

Design AI solutions that use multiple Dynamics 365 apps

Evaluate the costs and benefits of an AI-powered business solution

• Select ROI criteria for AI-powered business solutions, including the total cost of ownership

• Create an ROI analysis for the proposed AI solution for a business process

• Analyze whether to build, buy, or extend AI components for business solutions

• Implement a model router to intelligently route requests to the most suitable model

Select ROI criteria for AI-powered business solutions, including the total cost of ownership

Create an ROI analysis for the proposed AI solution for a business process

Analyze whether to build, buy, or extend AI components for business solutions

Implement a model router to intelligently route requests to the most suitable model

Design AI-powered business solutions (25–30%)

Design AI and agents for business solutions

• Design business terms for Copilot in Dynamics 365 apps for customer experience and service

• Design customizations of Copilot in Dynamics 365 apps for customer experience and service

• Design connectors for Copilot in Dynamics 365 Sales

• Design agents for integration with Dynamics 365 Contact Center channels

• Design task agents

• Design autonomous agents

• Design prompt and response agents

• Propose Microsoft AI services for a given requirement

• Propose code-first generative pages and the use of an agent feed for apps

• Design topics for Copilot Studio, including fallback

• Design data processing for AI models and grounding

• Design a business process to include AI components in a Power Apps canvas app

• Apply the Microsoft Power Platform Well-Architected Framework to intelligent application workloads

• Determine when to use standard natural language processing, Azure conversational language understanding, or generative AI orchestration in Copilot Studio

• Design agents and agent flows with Copilot Studio

• Design prompt actions in Copilot Studio

Design business terms for Copilot in Dynamics 365 apps for customer experience and service

Design customizations of Copilot in Dynamics 365 apps for customer experience and service

Design connectors for Copilot in Dynamics 365 Sales

Design agents for integration with Dynamics 365 Contact Center channels

Design task agents

Design autonomous agents

Design prompt and response agents

Propose Microsoft AI services for a given requirement

Propose code-first generative pages and the use of an agent feed for apps

Design topics for Copilot Studio, including fallback

Design data processing for AI models and grounding

Design a business process to include AI components in a Power Apps canvas app

Apply the Microsoft Power Platform Well-Architected Framework to intelligent application workloads

Determine when to use standard natural language processing, Azure conversational language understanding, or generative AI orchestration in Copilot Studio

Design agents and agent flows with Copilot Studio

Design prompt actions in Copilot Studio

Design extensibility of AI solutions

• Design AI solutions by using custom models in Azure AI Foundry

• Design agents in Microsoft 365 Copilot

• Design agent extensibility in Copilot Studio

• Design agent extensibility with Model Context Protocol in Copilot Studio

• Design agents to automate tasks in apps and websites by using Computer Use in Copilot Studio

• Design agent behaviors in Copilot Studio, including reasoning and voice mode

• Optimize solution design by using agents in Microsoft 365, including Teams and SharePoint

Design AI solutions by using custom models in Azure AI Foundry

Design agents in Microsoft 365 Copilot

Design agent extensibility in Copilot Studio

Design agent extensibility with Model Context Protocol in Copilot Studio

Design agents to automate tasks in apps and websites by using Computer Use in Copilot Studio

Design agent behaviors in Copilot Studio, including reasoning and voice mode

Optimize solution design by using agents in Microsoft 365, including Teams and SharePoint

Orchestrate configuration for prebuilt agents and apps

• Orchestrate AI in Dynamics 365 apps for finance and supply chain

• Orchestrate AI in Dynamics 365 apps for customer experience and service

• Propose Microsoft 365 agents for business scenarios

• Orchestrate the configuration of Microsoft 365 Copilot for Sales and Microsoft 365 Copilot for Service

• Propose Microsoft Power Platform AI features, including AI hub

• Design interoperability of the finance and operations agent chats to use additional knowledge sources

• Recommend the process of adding knowledge sources to in-app help and guidance for Dynamics 365 Finance or Dynamics 365 Supply Chain Management apps

Orchestrate AI in Dynamics 365 apps for finance and supply chain

Orchestrate AI in Dynamics 365 apps for customer experience and service

Propose Microsoft 365 agents for business scenarios

Orchestrate the configuration of Microsoft 365 Copilot for Sales and Microsoft 365 Copilot for Service

Propose Microsoft Power Platform AI features, including AI hub

Design interoperability of the finance and operations agent chats to use additional knowledge sources

Recommend the process of adding knowledge sources to in-app help and guidance for Dynamics 365 Finance or Dynamics 365 Supply Chain Management apps

Deploy AI-powered business solutions (40–45%)

Analyze, monitor, and tune AI-powered business solutions

• Recommend the process and tools required for monitoring agents

• Analyze backlog and user feedback of AI and agent usage

• Apply AI-based tools to analyze and identify issues and perform tuning

• Monitor agent performance and metrics

• Interpret telemetry data for performance and model tuning

Recommend the process and tools required for monitoring agents

Analyze backlog and user feedback of AI and agent usage

Apply AI-based tools to analyze and identify issues and perform tuning

Monitor agent performance and metrics

Interpret telemetry data for performance and model tuning

Manage the testing of AI-powered business solutions

• Recommend the process and metrics to test agents

• Create validation criteria of custom AI models

• Validate effective Copilot prompt best practices

• Design end-to-end test scenarios of AI solutions that use multiple Dynamics 365 apps

• Build the strategy for creating test cases by using Copilot

Recommend the process and metrics to test agents

Create validation criteria of custom AI models

Validate effective Copilot prompt best practices

Design end-to-end test scenarios of AI solutions that use multiple Dynamics 365 apps

Build the strategy for creating test cases by using Copilot

Design the ALM process for AI-powered business solutions

• Design the ALM process for data used in AI models and agents

• Design the ALM process for Copilot Studio agents, connectors, and actions

• Design the ALM process for Azure AI services agents

• Design the ALM process for custom AI models

• Design the ALM process for AI in Dynamics 365 apps for finance and supply chain

• Design the ALM process for AI in Dynamics 365 apps for customer experience and service

Design the ALM process for data used in AI models and agents

Design the ALM process for Copilot Studio agents, connectors, and actions

Design the ALM process for Azure AI services agents

Design the ALM process for custom AI models

Design the ALM process for AI in Dynamics 365 apps for finance and supply chain

Design the ALM process for AI in Dynamics 365 apps for customer experience and service

Design responsible AI, security, governance, risk management, and compliance

• Design security for agents

• Design governance for agents

• Design model security

• Analyze solution and AI vulnerabilities and mitigations, including prompt manipulation

• Review solution for adherence to responsible AI principles

• Validate data residency and movement compliance

• Design access controls on grounding data and model tuning

• Design audit trails for changes to models and data

Design security for agents

Design governance for agents

Design model security

Analyze solution and AI vulnerabilities and mitigations, including prompt manipulation

Review solution for adherence to responsible AI principles

Validate data residency and movement compliance

Design access controls on grounding data and model tuning

Design audit trails for changes to models and data