Official study guide · 2026 Edition

The RESAIA AI Governance Body of Knowledge

The disciplines that make up AI governance each evolved independently. The RESAIA Body of Knowledge teaches them as one connected discipline across traditional machine learning, generative AI, and agentic systems.

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Chapters: 16
Governance domains: 14
First edition: 2026

Inside the book

What the Body of Knowledge covers

Sixteen chapters are organised across a four-layer governance architecture. Two foundation chapters establish the conceptual and structural groundwork; fourteen pillar chapters teach the governance disciplines.

01
Foundations
Chapters 1-2
The shared foundation
Establishes the shared vocabulary, the four-layer governance model, and the cross-domain integration logic that connects every chapter that follows.
02
Governance Foundation
Chapters 3-5
Why do we govern AI?
The strategic, regulatory, and ethical basis for AI governance.
03
Safeguard
Chapters 6-9
What could go wrong?
The disciplines that identify, prevent, and mitigate AI-specific risks.
04
Operate
Chapters 10-12
How do we put governance into practice?
The disciplines that govern AI systems through their lifecycle.
05
Assure
Chapters 13-16
How do we prove it?
The disciplines that verify governance is working.

Certification preparation

The base material for every RESAIA certification

Every RESAIA certification is grounded in the Body of Knowledge. Candidates study the relevant chapters, prepare with available guides and practice exams, and sit the certification exam.

AIGP

AI Governance Professional

Examines: All 16 chapters

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ARMP

AI Risk Management Professional

Primary material: Chapter 6
Supporting material: Chapters 3, 5, 10, and 14

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AISP

AI Security Professional

Primary material: Chapter 7
Supporting material: Chapters 6, 9, 11, and 15

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AAAP

AI Audit & Assurance Professional

Primary material: Chapter 16
Supporting material: Chapters 4, 13, 14, and 15

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APGP

AI Privacy & Data Governance Professional

Primary material: Chapter 8
Supporting material: Chapters 5, 6, 9, and 11

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AIPP

AI Procurement Professional

Primary material: Chapter 9
Supporting material: Chapters 3, 6, 7, and 8

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Why this book exists

One discipline, built for practice

Scattered Knowledge

Risk, compliance, security, ethics, legal, procurement, audit, and data privacy each developed their own knowledge base. The Body of Knowledge connects them across fourteen governance domains.

Theory Without Practice

Principles and regulations tell organisations what to value and what to comply with. The Body of Knowledge provides operational methods, core activities, control frameworks, and metrics that can be adopted directly.

Knowledge Serves Humanity

AI will affect everyone. How it is governed will be decided by practitioners, educators, and policymakers. The Body of Knowledge is their shared reference.

Who it is written for

A reference for every role that governs AI

AI governance leads and Chief AI Officers

End-to-end governance programme design, policy architecture, accountability structures, maturity assessment, and cross-domain integration.

Risk and compliance professionals

AI-specific risk taxonomies, control-to-risk mappings, risk treatment methods, and assurance evidence that integrate with enterprise frameworks.

CISOs and data protection officers

AI threat landscapes, adversarial resilience, data quality and lineage governance, privacy obligations, and security implications across AI architectures.

Procurement and vendor management professionals

Vendor risk tiering, AI-specific due diligence, contractual governance, foundation model oversight, and approved vendor register management.

Board members

Strategic oversight, governance policy architecture, risk appetite calibration, and reporting structures for AI oversight responsibilities.

Internal and external auditors

AI audit programme design, evidence collection, conformity assessment, compliance verification, and the Responsible Governance Maturity Model.

Data scientists and ML engineers

Lifecycle gates, documentation obligations, monitoring expectations, and the governance rationale behind production controls.

Put the Body of Knowledge into practice

Build role-specific capability through RESAIA certifications grounded in one connected AI governance discipline.

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