Exam Mapping

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Exam Mapping

This page shows exactly which lesson teaches each skill the AIGP exam tests. Use it to find a lesson for a specific exam skill, or to see how many questions a block of the exam carries.

How the exam is structured

The exam is organized into 4 domains — the broad areas of AI governance knowledge. Each domain splits into competencies(the “blocks” below, such as I.A or II.C) — a named cluster of related skills. Each competency lists one or more Performance Indicators (PIs) — the specific, gradable skill a question can test, such as II.A.2(“apply data minimisation and privacy by design to AI”).

Every exam question is written against exactly one PI. Each domain and competency also carries an official question range — the minimum and maximum number of scored questions that domain or competency contributes to the exam. Together, the 58 PIs below add up to a 77–93-question exam.

How to read this page: open a domain, find the competency block, and match the PI code to the lesson chip on the right. If you are weak on a specific PI, that chip tells you exactly where to study.

Understanding the foundations of AI governance

3 blocks · 12 PIs · 16–20 questions on the exam

I.A

What AI is and why it needs governance

4–6 questions

I.A.1Define artificial intelligence and distinguish the major types of AI systems.

No lesson mapped

I.A.2Identify the risks and harms AI poses to individuals, groups, organizations and society, including misalignment with objectives, ethics and bias risk, and problems of complexity and scalability.

No lesson mapped

I.A.3Explain the characteristics of AI that demand a comprehensive governance approach: complexity, opacity, autonomy, speed and scale, potential for harm or misuse, data dependency, and probabilistic versus deterministic outputs.

No lesson mapped

I.A.4Describe and apply responsible-AI principles: fairness; safety and reliability; privacy; security and robustness; transparency and explainability; accountability; and human-centricity.

No lesson mapped

I.B

Establishing and communicating organizational expectations

5–7 questions

I.B.1Define roles and responsibilities for the full set of AI governance stakeholders.

No lesson mapped

I.B.2Establish cross-functional collaboration in the AI governance program, for effectiveness and for diversity of expertise and perspective.

No lesson mapped

I.B.3Create and deliver a training and awareness program for all stakeholders covering AI terminology, strategy and governance.

No lesson mapped

I.B.4Differentiate the governance approach by organizational size, maturity, industry, products and services, objectives and risk tolerance.

No lesson mapped

I.C

Policies and procedures across the AI life cycle

6–8 questions

I.C.1Create and implement policies that ensure oversight and accountability across all AI life-cycle stages: use-case assessment, risk management, ethics by design, data acquisition and use, development, training and testing, deployment and monitoring, documentation and reporting, and incident management.

No lesson mapped

I.C.2Evaluate and update existing privacy, security, data-governance and intellectual-property policies to address AI.

No lesson mapped

I.C.3Create and apply policies, assessments and contracts to manage third-party risk, including procurement, supply chain, human resources and acceptable use.

No lesson mapped

Understanding how laws, standards and frameworks apply to AI

4 blocks · 17 PIs · 19–23 questions on the exam

II.A

Existing data privacy laws and AI

4–6 questions

II.A.1Apply the core privacy principles of transparency, choice, lawful basis and purpose limitation to AI systems.

No lesson mapped

II.A.2Apply data minimization and privacy by design to the development and use of AI.

No lesson mapped

II.A.3Map controller obligations to AI: DPIAs, processor arrangements, cross-border transfers, data-subject rights, automated decision-making rules, breach notification and record-keeping.

III

Understanding how to govern AI development

3 blocks · 16 PIs · 21–25 questions on the exam

III.A

Governing design and build

6–8 questions

III.A.1Define the business context and use case for an AI system.

No lesson mapped

III.A.2Conduct an impact assessment during design.

No lesson mapped

III.A.3Apply organizational policies and ethical principles to design: architecture and model selection, human oversight, data analysis, metrics and thresholds, stakeholder engagement and operational controls.

No lesson mapped

Understanding how to govern AI deployment and use

3 blocks · 13 PIs · 21–25 questions on the exam

IV.A

Evaluating factors and risks before deployment

6–8 questions

IV.A.1Evaluate use-case context: objectives, required performance, data availability, ethical considerations and workforce readiness.

No lesson mapped

IV.A.2Compare model types: classic vs generative, proprietary vs open source, small vs large, language vs multimodal.

No lesson mapped

IV.A.3Compare deployment options: cloud, on-premises or edge; used as-is or adapted via fine-tuning, retrieval-augmented generation or agentic patterns.

58 performance indicators total · AIGP Body of Knowledge v2.1 (effective 2 February 2026) · 77–93 scored questions across 4 domains

How the exam is structured

Understanding the foundations of AI governance

What AI is and why it needs governance

Establishing and communicating organizational expectations

Policies and procedures across the AI life cycle

Understanding how laws, standards and frameworks apply to AI

Existing data privacy laws and AI

Understanding how to govern AI development

Governing design and build

Understanding how to govern AI deployment and use

Evaluating factors and risks before deployment

Other existing laws and AI

Main elements of AI-specific laws

Main standards and frameworks

Governing data in training and testing

Governing release, monitoring and maintenance

Assessing the AI system

Governing deployment and use