AB-731 cheat sheet
A one-page reference for the Microsoft AI Transformation Leader exam: the format, how the domains are weighted, and the glossary terms for this exam.
Exam at a glance
Vendor
Microsoft
Level
Foundational
Questions
60
Time
45 min
Mock pass mark
70%
Domains
3
Practice Qs
145
Code
AB-731
Domain weightings
How much of the exam each domain covers. Spend your study time in proportion — the heavier the domain, the more questions you'll see.
Key terms
- Generative AI
- Generative AI is a class of AI that produces new content such as text, images, and code from patterns learned in training. AB-731 covers the business value of generative AI and how it differs from other types of AI.
- Microsoft 365 Copilot
- Microsoft 365 Copilot is the generative AI assistant embedded across Microsoft 365 apps that grounds responses in your work data. AB-731 covers mapping business processes and use cases to Copilot.
- Microsoft Copilot Studio
- Microsoft Copilot Studio is the low-code platform for building and customizing agents and copilots. AB-731 covers understanding its capabilities as part of Microsoft's AI apps and services.
- Microsoft Graph
- Microsoft Graph is the data layer that exposes Microsoft 365 content and signals and grounds Copilot responses in your organization's data. AB-731 covers understanding its capabilities.
- Foundry Tools
- Foundry Tools are the Azure AI capabilities — including Azure Vision in Foundry Tools, Azure AI Search, and Microsoft Foundry — mapped to business needs. AB-731 covers identifying their benefits and capabilities.
- Prompt engineering
- Prompt engineering is the practice of crafting effective instructions to get better results from a generative model. AB-731 covers the impact and techniques of prompt engineering.
- RAG
- RAG (retrieval-augmented generation) grounds a generative model's answers in retrieved business data to improve accuracy. AB-731 covers understanding how RAG is used for AI solutions.
- Grounding
- Grounding is anchoring an AI response in relevant, trusted data so it reflects your business context. AB-731 covers identifying the business requirements for grounding solutions.
- Fabrication
- A fabrication is a plausible-sounding but incorrect output produced by a generative model. AB-731 covers fabrications among the challenges of using generative AI solutions.
- Responsible AI
- Responsible AI is Microsoft's set of principles — fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability — for trustworthy AI. AB-731 covers aligning an AI strategy with responsible AI policies.
- AI council
- An AI council is a cross-functional governance body that guides AI strategy, oversight, and alignment across an organization. AB-731 covers establishing one as part of responsible AI governance.
- AI champions program
- An AI champions program is an adoption initiative that develops internal advocates to drive AI usage across teams. AB-731 covers establishing one to plan for AI adoption.
- Researcher
- Researcher is a Microsoft 365 Copilot agent that performs deep, multi-step research across work and web sources. AB-731 covers identifying when to use Researcher or Analyst in Copilot.
- Analyst
- Analyst is a Microsoft 365 Copilot agent that reasons over data to produce analysis and insights for decisions. AB-731 covers identifying when to use Researcher or Analyst in Copilot.
- Total cost of ownership
- Total cost of ownership (TCO) is the full cost of an AI solution over its lifetime, including licensing, usage tokens, and operations. AB-731 covers cost drivers and ROI considerations in generative AI usage.