Domain I in one pass: foundations, roles, and program policies
Lesson 1 of 4 in AIGP Domains I–II Recap: Foundations, Laws, Standards, and Frameworks.
This module is a recap, not a course. Everything Domain I tests is taught in full in the Foundations track; everything Domain II tests lives in the EU AI Act, ISO, NIST/US, and Global tracks. What you get here is the exam’s-eye view: which competency asks what, where candidates lose points, and exactly which module to reopen when a practice question exposes a gap.
Domain I — Understanding the foundations of AI governance — supplies 16–20 questions across three competencies. It is the lightest domain, but it is also the cheapest place to be perfect: its questions are the most predictable on the exam.
| Competency | What the questions actually ask | Study module |
|---|---|---|
I.A — AI foundations, risks, principles (4–6 q) | Pick the right AI type from a description (rule-based vs ML; supervised vs unsupervised vs reinforcement; generative; agentic). Name the unique characteristic — opacity, autonomy, data dependency, probabilistic output, speed and scale — that makes a scenario a governance problem. Match a responsible-AI principle (fairness, safety, privacy, transparency, accountability, human-centricity) to the control that operationalises it. | Foundations: What Is AI · Harms and Risks · Ethics and Trustworthy AI |
I.B — roles and program design (5–7 q) | Distinguish developers, providers, deployers, and users and assign the governance duty to the right one. Design cross-functional collaboration (why the ethics committee needs engineers and lawyers and affected-community input). Scale a governance approach to company size, maturity, industry, and risk appetite. Spot what a training-and-awareness program must cover. | Foundations: Who’s Who · How Governance Works |
I.C — policies across the life cycle (6–8 q) | Given a life-cycle stage, name the policy or artifact that governs it — use-case intake, data acquisition, training and testing, deployment, monitoring, incident management. Decide when an existing policy (privacy, security, IP) needs an AI update versus a new policy. Manage third-party risk through procurement terms, acceptable-use policies, and supply-chain clauses. | Foundations: AI Lifecycle · Operations: Inventory and Intake |
Interactive sorting exercise: Each card paraphrases a real AIGP-style question task. Sort it into the competency it drills — this trains you to recognise what a question is really testing.
Interactive checkpoint quiz (1 questions) — open this page in a browser to take it.