Practice Exams | MS AB-100: Agentic AI Bus Sol Architect

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.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.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 glancePlan 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 solutionsAssess the use of agents in task automation, data analytics, and decision-makingReview data for grounding, including accuracy, relevance, timeliness, cleanliness, and availabilityOrganize business solution data to be available for other AI systemsDesign overall AI strategy for business solutionsImplement the AI adoption process from the Cloud Adoption Framework for AzureDesign the strategy for building AI and agents in business solutionsDesign a multi-agent solution by using platforms such as Microsoft 365 Copilot, Copilot Studio, and Azure AI FoundryDevelop the use cases for prebuilt agents in the solutionDefine the solution rules and constraints when building AI components with Copilot Studio, Azure AI services, and Azure AI FoundryDetermine the use of generative AI and knowledge sources in agents built with Copilot StudioDetermine when to build custom agents or extend Microsoft 365 CopilotDetermine when custom AI models should be createdProvide guidelines for creating a prompt libraryDevelop the use cases for customized small language models for the solutionProvide prompt engineering guidelines and techniques for AI-powered business solutionsInclude the elements of the Microsoft AI Center of ExcellenceDesign AI solutions that use multiple Dynamics 365 appsEvaluate the costs and benefits of an AI-powered business solutionSelect ROI criteria for AI-powered business solutions, including the total cost of ownershipCreate an ROI analysis for the proposed AI solution for a business processAnalyze whether to build, buy, or extend AI components for business solutionsImplement a model router to intelligently route requests to the most suitable modelDesign AI-powered business solutions (25–30%)Design AI and agents for business solutionsDesign business terms for Copilot in Dynamics 365 apps for customer experience and serviceDesign customizations of Copilot in Dynamics 365 apps for customer experience and serviceDesign connectors for Copilot in Dynamics 365 SalesDesign agents for integration with Dynamics 365 Contact Center channelsDesign task agentsDesign autonomous agentsDesign prompt and response agentsPropose Microsoft AI services for a given requirementPropose code-first generative pages and the use of an agent feed for appsDesign topics for Copilot Studio, including fallbackDesign data processing for AI models and groundingDesign a business process to include AI components in a Power Apps canvas appApply the Microsoft Power Platform Well-Architected Framework to intelligent application workloadsDetermine when to use standard natural language processing, Azure conversational language understanding, or generative AI orchestration in Copilot StudioDesign agents and agent flows with Copilot StudioDesign prompt actions in Copilot StudioDesign extensibility of AI solutionsDesign AI solutions by using custom models in Azure AI FoundryDesign agents in Microsoft 365 CopilotDesign agent extensibility in Copilot StudioDesign agent extensibility with Model Context Protocol in Copilot StudioDesign agents to automate tasks in apps and websites by using Computer Use in Copilot StudioDesign agent behaviors in Copilot Studio, including reasoning and voice modeOptimize solution design by using agents in Microsoft 365, including Teams and SharePointOrchestrate configuration for prebuilt agents and appsOrchestrate AI in Dynamics 365 apps for finance and supply chainOrchestrate AI in Dynamics 365 apps for customer experience and servicePropose Microsoft 365 agents for business scenariosOrchestrate the configuration of Microsoft 365 Copilot for Sales and Microsoft 365 Copilot for ServicePropose Microsoft Power Platform AI features, including AI hubDesign interoperability of the finance and operations agent chats to use additional knowledge sourcesRecommend the process of adding knowledge sources to in-app help and guidance for Dynamics 365 Finance or Dynamics 365 Supply Chain Management appsDeploy AI-powered business solutions (40–45%)Analyze, monitor, and tune AI-powered business solutionsRecommend the process and tools required for monitoring agentsAnalyze backlog and user feedback of AI and agent usageApply AI-based tools to analyze and identify issues and perform tuningMonitor agent performance and metricsInterpret telemetry data for performance and model tuningManage the testing of AI-powered business solutionsRecommend the process and metrics to test agentsCreate validation criteria of custom AI modelsValidate effective Copilot prompt best practicesDesign end-to-end test scenarios of AI solutions that use multiple Dynamics 365 appsBuild the strategy for creating test cases by using CopilotDesign the ALM process for AI-powered business solutionsDesign the ALM process for data used in AI models and agentsDesign the ALM process for Copilot Studio agents, connectors, and actionsDesign the ALM process for Azure AI services agentsDesign the ALM process for custom AI modelsDesign the ALM process for AI in Dynamics 365 apps for finance and supply chainDesign the ALM process for AI in Dynamics 365 apps for customer experience and serviceDesign responsible AI, security, governance, risk management, and complianceDesign security for agentsDesign governance for agentsDesign model securityAnalyze solution and AI vulnerabilities and mitigations, including prompt manipulationReview solution for adherence to responsible AI principlesValidate data residency and movement complianceDesign access controls on grounding data and model tuningDesign audit trails for changes to models and data