IAPP – AIGP Exam Analysis

I would like to share my experience with the AIGP as there is interest from candidates looking to complete the exam soon, I had the chance to use official study material and practice exam from IAPP

General Overview and my personal experience

• Studied for approximately 3 months.
• Studied extensively for approximately 1 month.
• Registration process took me 15-20 min.
• I arrived earlier than expected and was able to start my test 30 minutes prior to the scheduled time.
• Completed the exam in 2 hours (allocated almost 3 hours).
• Took the exam at a center close to home.
• Took a 5-minute break, which took longer than expected due to security checks and finding my seat. This disrupted my concentration and momentum.
• The exam is divided into two sections of 50 questions, with a break in the middle.
• You can review questions from the first 50 and submit, but cannot go back to them later.
• Hesitated in answers to 10+ questions (2 answers discarded, 2 answers potentially valid)
• Completed the IAPP practice exam at least 3 times (first score 75%, third 90% or more).
• Completed 3 out of 5 practice exams purchased from Udemy.
• Before accessing the official material, I listened to numerous webinars related to NIST and the EU AI Act.

The Exam Was More Difficult Than Anticipated

• Studying solely with the official IAPP material is insufficient (you can cover 70-80% of what is needed)
• Official study material provides a general understanding, but additional depth is needed.
• The exam is based on the Book of Knowledge; follow the items listed there.
• Pay attention to the number of items per domain and allocate more time to the larger ones.
• Practice exams were slightly easier (passing with 85% or more may indicate success).
• My AI/ML knowledge was insufficient, and I struggled with questions related to associated terms and definitions.
• There are at least 6 case studies (each with 2-5 questions).
• Relying solely on IAPP material led to repetition and memorization rather than deep understanding.
• Take practice exams at the end to avoid memorizing them.
• Obtain additional practice exams online.
• Completed 3 out of 5 practice exams purchased from Udemy.
• Listen to material from other authors at least once.
• Review other IAPP releases (reports, notes, etc.).
• The AI Glossary from IAPP is relevant, as many questions are about concepts (they may create definitions or introduce unrelated names or concepts that sound legitimate).

Exam Structure and Content (not far from the BoK)

Technical

• ML/AI types of models
• Differentiating models used in different contexts
• Understanding each stage of the lifecycle: planning, design, implementation, post-implementation
• Concepts associated with ML/AI

Regulatory and Frameworks

• Determining when to use which frameworks
• Identifying similarities between regulations and frameworks
• While my exam did not include questions on penalties, it is recommended to have an understanding.
• Coverage included: GDPR, EU AI Act, White House directives, Singapore approach, Canadian proposed regulation, China, NIST, IEEE, ISO, and other frameworks

Implications of Implementation

• Considering the context of implementation (industries, size, etc.), treat it as a product
• Understanding penalties, documentation requirements, stakeholder management, ethics, fairness, trustworthiness, reputation and other risk management, and more.