Free Practice Questions for Microsoft AI Transformation Leader (AB-731) Certification

    🔄 Last checked for updates June 30th, 2026

    Study with 341 exam-style practice questions designed to help you prepare for the Microsoft AI Transformation Leader (AB-731).

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    Exam Details

    Key information about Microsoft AI Transformation Leader (AB-731)

    Official study guide

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    Question formats CertSafari offers
    • Multiple choice
    • Ordering
    • Matching
    • True/False
    • Fill in the blank
    prerequisites:

    Experience leading adoption or change management in a business context; familiarity with Microsoft 365 services, Microsoft Foundry, and general AI capabilities

    target audience:

    Business decision-makers at all levels responsible for guiding transformation and innovation within their teams or organizations

    Exam Topics & Skills Assessed

    Skills measured (from the official study guide)

    Identify the business value of generative AI solutions (35–40%)(35–40%)

    Identify the foundational concepts of generative AI

    • Differentiate generative AI from other AI types
    • Select generative AI for business needs
    • Describe AI model differences (fine-tuned, pretrained)
    • Explain generative AI cost drivers (tokens, ROI)
    • Identify generative AI challenges (fabrications, bias)
    • Identify generative AI business value (scalability, automation)

    Identify benefits and capabilities of generative AI solutions

    • Describe prompt engineering impact
    • Understand prompt engineering techniques
    • Identify grounding solution requirements
    • Understand RAG for AI solutions
    • Understand data impact on AI (type, quality)
    • Describe secure AI importance
    • Identify machine learning value scenarios
    • Describe ML solution lifecycle
    • Identify AI system security considerations

    Identify benefits, capabilities, and opportunities for Microsoft’s AI apps and services (35–40%)(35–40%)

    Identify benefits and capabilities of Microsoft 365 Copilot and Microsoft Copilot

    • Map business processes to Copilot
    • Understand Copilot version differences
    • Understand Copilot Chat web/mobile capabilities
    • Understand Copilot in Microsoft 365 apps
    • Understand Microsoft Copilot Studio
    • Understand Microsoft Graph
    • Identify integrated Microsoft AI benefits
    • Map business processes to Microsoft AI
    • Identify Researcher/Analyst use in Copilot
    • Identify build, buy, extend (Copilot extensibility)

    Identify benefits and capabilities of Foundry Tools

    • Map business processes to Foundry Tools
    • Identify Foundry Tools capabilities (Azure Vision, AI Search)
    • Match AI model to business need
    • Identify Microsoft Foundry/Tools benefits

    Identify an implementation and adoption strategy for Microsoft’s AI apps and services (20–25%)(20–25%)

    Align an AI strategy with Microsoft responsible AI policies

    • Explain responsible AI importance
    • Establish AI governance principles
    • Establish AI council for strategy
    • Ensure AI solutions meet responsible AI standards

    Plan for AI adoption across the organization

    • Establish AI adoption team
    • Identify AI adoption barriers
    • Establish AI champions program
    • Understand data, security, privacy, cost impacts
    • Understand Copilot license types
    • Understand Foundry Tools subscription models

    Techniques & products

    Generative AI
    AI models
    Fine-tuned models
    Pretrained models
    Prompt engineering
    Retrieval-Augmented Generation (RAG)
    Machine learning
    Secure AI
    Microsoft 365 Copilot
    Microsoft Copilot
    Microsoft Copilot Chat
    Microsoft Copilot Studio
    Microsoft Graph
    Foundry Tools
    Azure Vision
    Azure AI Search
    Microsoft Foundry
    Responsible AI
    AI governance
    AI council
    Copilot license types
    Foundry Tools subscription models

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