AIGP Body of Knowledge 2026 explained
The 2026 AIGP Body of Knowledge has four connected domains. It moves from AI-governance foundations, through laws and standards, into development controls, then deployment and ongoing use. Treat it as one lifecycle, not four isolated reading lists.
The four domains at a glance
| Domain | What it asks you to understand | What to practice |
|---|---|---|
| I. Foundations of AI governance | Why AI needs governance, organisational expectations, policies and lifecycle procedures | Roles, accountability, governance structures and risk appetite |
| II. Laws, standards and frameworks | Privacy law, other existing law, AI-specific law, standards and governance tools | Choosing the applicable instrument and explaining what it changes |
| III. Governing AI development | Design, building, training and testing data, release, monitoring and maintenance | Controls before deployment, documentation, testing and change management |
| IV. Governing AI deployment and use | Deployment decisions, assessment activities, use controls and oversight | Whether to deploy, how to monitor and when to escalate or stop |
How the domains connect
- Set expectations. Decide ownership, acceptable use and escalation routes.
- Map obligations. Identify applicable law, standards, contracts and internal policy.
- Control development. Govern data, design choices, testing, documentation and release.
- Control deployment. Assess context, users, impact, human oversight and residual risk.
- Monitor change. Track performance, incidents, drift, new uses and regulatory change.
What scenario questions usually test
A scenario rarely asks only for a definition. It normally describes an organisation, an AI use, an affected group and a lifecycle stage. The strongest answer identifies the governance gap and selects the next proportionate control.
| Scenario signal | Likely governance response |
|---|---|
| No clear owner | Assign accountable roles and an escalation path |
| Training data of uncertain origin | Check provenance, rights, representativeness and data governance |
| High-impact deployment | Run the relevant impact and risk assessments before release |
| Model behaviour changed | Investigate drift, validate performance and apply change control |
| New use after approval | Reassess purpose, affected people, legal duties and residual risk |
A practical study sequence
- Read the current outline and mark every unfamiliar verb.
- Build one lifecycle diagram linking governance actions to stages.
- Make comparison tables for laws, standards and frameworks.
- Practice scenarios that force a choice between controls.
- Review wrong answers by governance gap, not by question number.
Common mistakes when using the Body of Knowledge
Do not treat the four areas as isolated lists. A realistic scenario can require a legal classification, governance role, development control and deployment decision at the same time.
Primary source
Reviewed 29 August 2026. This independent explanation does not reproduce or replace the IAPP outline.
Continue with the AIGP study guide or use the exam-style question bank.
Sources and study method
This independent study material uses the current published AIGP outline, active recall, spaced retrieval and scenario practice. Read the full method. Current sources are identified in the article.
Frequently asked questions
How many domains are in the 2026 AIGP Body of Knowledge?
The 2026 outline groups the Body of Knowledge into four domains covering foundations, law and standards, AI development, and AI deployment and use.
Is the AIGP exam only about the EU AI Act?
No. The Body of Knowledge also covers governance structures, risk management, standards, data and model development, assessment, monitoring, deployment and organisational controls.
What is the best way to study the AIGP Body of Knowledge?
Use the four domains as a map, then practice choosing governance actions at each AI lifecycle stage. Memorising definitions alone is insufficient for scenario questions.