This AIGP (AI Governance Professional) Practice Test course is designed to give you the ultimate preparation experience for the IAPP’s AIGP certification exam. With 600 high-quality, exam-like questions divided across the four official AIGP exam domains, this course replicates the real test environment and helps you build mastery and confidence.

Each question has been carefully crafted to reflect the difficulty, style, and topics of the actual exam, including scenario-based and theory-based questions. Whether you're just starting your AIGP prep or need a final assessment before test day, this course will help you identify your strengths and target your weak areas.

Key Features of the Course

• 600 AIGP Practice Questions aligned to the official IAPP exam blueprint

• Questions are categorized by domain for focused preparation

• Timed exams to simulate the actual 3-hour test environment

• Instant scoring and performance reports after each test

• Detailed explanations for every option – not just the correct one

• Scenario-based, policy-based, and theory questions included

• Build confidence and boost your readiness for the AIGP exam

600 AIGP Practice Questions aligned to the official IAPP exam blueprint

Questions are categorized by domain for focused preparation

Timed exams to simulate the actual 3-hour test environment

Instant scoring and performance reports after each test

Detailed explanations for every option – not just the correct one

Scenario-based, policy-based, and theory questions included

Build confidence and boost your readiness for the AIGP exam

Exam Domains Covered

All questions are divided according to the official AIGP domains defined by IAPP:

Understanding the foundations of AI governance
(~18–20% of exam)
Ethics, risk, governance frameworks, and responsible AI foundations.

Understanding how laws, standards, and frameworks apply to AI
(~24–26% of exam)
Privacy laws, EU AI Act, NIST, ISO standards, OECD AI principles.

Understanding how to govern AI development
(~27–29% of exam)
Data quality, model training, lifecycle controls, internal processes.

Understanding how to govern AI deployment and use
(~27–29% of exam)
Vendor risk, transparency, post-deployment controls, auditing.