AIGP knowledge map
You don’t need a law degree to govern AI systems, but you do need to know what the exam’s four domains demand: the principles of responsible AI, the laws and frameworks that apply, how development gets governed, and how deployment and use are kept honest. This map points each domain to the guidebook lessons that teach the underlying material — from how LLM applications are built to the EU AI Act and the NIST AI Risk Management Framework. The exam itself is paid; everything this map teaches is free. Domain titles are IAPP’s; everything else is the guidebook’s own words.
Published 2026-10-09 · generated from the lesson data · 4 of 4 domains have a lesson
This map follows the AIGP Body of Knowledge version 2.1 (effective February 2, 2026), verified against IAPP’s official PDF on 2026-10-10.
The AIGP exam is a paid exam. This map teaches the four domains from free guidebook lessons; it is not the exam.
The domains
| Domain | Title | Lessons |
|---|---|---|
| I | Understanding the foundations of AI governance | How LLM applications are built and where they are attacked, Governing AI, Security policy, standards, procedures, and guidelines: the document hierarchy, Security awareness, education, and training: building the learning program |
| II | Understanding how laws, standards and frameworks apply to AI | Governing AI, Legal, regulatory, and compliance: mapping obligations to evidence |
| III | Understanding how to govern AI development | AI attacks and defenses in the build pipeline, AI supply chain security, Threat modeling AI systems, Secure SDLC: catching the vulnerability before it ships, The data lifecycle: from collection to destruction |
| IV | Understanding how to govern AI deployment and use | Governing AI, Incident management: the team, the escalation, and the communications, Logging and monitoring operations: deciding what gets watched, and by whom, Security metrics: measuring the program without lying to yourself |