AIGP Domain1 Training Video

Preparing for the IAPP AIGP certification? This full training module walks you through Domain I — Foundations of AI Governance, the vocabulary layer that every other exam domain builds on. No prerequisites, no coding — just 27 minutes of structured, exam-focused teaching with real industry data. What you'll learn: • What legally counts as an "AI system" (OECD / EU AI Act definition) — and the 4 output types you must memorize • The AI family tree: AI ⊃ ML ⊃ Deep Learning ⊃ Generative AI ⊃ Foundation Models ⊃ GPAI — and why GPAI ≠ AGI • The 6 traits that make AI harder to govern than normal software — and the control each one forces • The 6 responsible-AI principles, with the exam hook for each • How a governance program is actually built: 9 blocks, 3 lines of defense, and the proportionality rule the exam loves • The 4 actor roles (developer / provider / deployer / user) — and the 3 triggers that flip a deployer into a provider under Article 25 • How to govern third-party and supply-chain AI: build, buy, or borrow • 3 exam-style practice questions with full answer reasoning Chapters: 0:00 Welcome & module overview 0:52 Where Domain I sits in the exam 1:58 Why AI governance, in three numbers 3:11 What legally counts as an AI system 4:19 The AI family tree 5:32 Four distinctions that set your workload 6:56 Model vs. system — what the law regulates 8:02 Six traits that make AI hard to govern 9:31 The six responsible-AI principles 11:11 Case study: a hiring tool under stress 12:43 The nine-block governance program 14:34 Who owns AI risk: three lines of defense 15:48 Proportionality: right-sizing governance 17:11 The four actors 18:29 The hat-change: three Article 25 triggers 20:00 Third-party & supply-chain risk 21:33 Practice questions (pause here!) 22:55 Answers and the reasoning being tested 24:14 What to memorize and do this week 25:40 Wrap-up & Domain II preview