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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	Understanding the Foundations of AI Governance: This section of the exam measures skills of AI governance professionals and covers the core concepts of AI governance, including what AI is, why governance is needed, and the risks and unique characteristics associated with AI. It also addresses the establishment and communication of organizational expectations for AI governance, such as defining roles, fostering cross-functional collaboration, and delivering training on AI strategies. Additionally, it focuses on developing policies and procedures that ensure oversight and accountability throughout the AI lifecycle, including managing third-party risks and updating privacy and security practices.
Topic 2	Understanding How to Govern AI Development: This section of the exam measures the skills of AI project managers and covers the governance responsibilities involved in designing, building, training, testing, and maintaining AI models. It emphasizes defining the business context, performing impact assessments, applying relevant laws and best practices, and managing risks during model development. The domain also includes establishing data governance for training and testing, ensuring data quality and provenance, and documenting processes for compliance. Additionally, it focuses on preparing models for release, continuous monitoring, maintenance, incident management, and transparent disclosures to stakeholders.
Topic 3	Understanding How Laws, Standards, and Frameworks Apply to AI: This section of the exam measures skills of compliance officers and covers the application of existing and emerging legal requirements to AI systems. It explores how data privacy laws, intellectual property, non-discrimination, consumer protection, and product liability laws impact AI. The domain also examines the main elements of the EU AI Act, such as risk classification and requirements for different AI risk levels, as well as enforcement mechanisms. Furthermore, it addresses the key industry standards and frameworks, including OECD principles, NIST AI Risk Management Framework, and ISO AI standards, guiding organizations in trustworthy and compliant AI implementation.
Topic 4	Understanding How to Govern AI Deployment and Use: This section of the exam measures skills of technology deployment leads and covers the responsibilities associated with selecting, deploying, and using AI models in a responsible manner. It includes evaluating key factors and risks before deployment, understanding different model types and deployment options, and ensuring ongoing monitoring and maintenance. The domain applies to both proprietary and third-party AI models, emphasizing the importance of transparency, ethical considerations, and continuous oversight throughout the model’s operational life.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q75-Q80):

NEW QUESTION # 75
An artist has been using an AI tool to create digital art and would like to ensure that it has copyright protection in the United States. Which of the following is most likely to enable the artist to receive copyright protection?

A. Ensure the tool was trained using publicly available content.
B. Obtain a representation from the AI provider on how the tool works.
C. Provide a log of the prompts the artist used to generate the images.
D. Update the images in a creative way to demonstrate that it is the artist's.

Answer: D

Explanation:
Copyright protection typically requires a human author's creative input, so modifying AI-generated images in a creative way demonstrates the artist's originality needed for copyright.

NEW QUESTION # 76
The best method to ensure a comprehensive identification of risks for a new AI model is?

A. An impact assessment.
B. An environmental scan.
C. Red teaming.
D. Integration testing.

Answer: A

Explanation:
The most comprehensive way to identify a full range of risks - legal, ethical, operational, and societal - for a new AI model is through aformal impact assessment, such as aData Protection Impact Assessment (DPIA)orAlgorithmic Impact Assessment.
From theAI Governance in Practice Report 2025:
"Risk-based approaches are often distilled into organizational risk management efforts, which put impact assessments at the heart of deciding whether harm can be reduced." (p. 29)
"DPIAs... help organizations identify, analyze and minimize data-related risks and demonstrate accountability." (p. 30) A . Environmental scanis too general.
B . Red teamingis useful for adversarial risk but not broad.
C . Integration testingfocuses on technical/system compatibility, not overall risk.

NEW QUESTION # 77
Scenario:
A distributor operating in the EU is responsible for selling imported high-risk AI systems to businesses. The distributor wants to ensure they fulfill all applicable obligations under the EU AI Act.
All of the following are obligations of a distributor of high-risk AI systems under the EU AI Act EXCEPT?

A. Verification of CE marking
B. Registration in EU Database
C. Communication with national authorities
D. Corrective actions

Answer: B

Explanation:
The correct answer isC.Registration in the EU databaseis an obligation ofprovidersof high-risk AI systems- not distributors.
From the AIGP ILT Guide - Roles & Obligations Module:
"Distributors must verify CE marking, ensure instructions for use are provided, inform authorities of risks, and take corrective action when necessary. However, registration duties in the EU database lie with the provider." Also from the AI Governance in Practice Report2025:
"The AI Act differentiates responsibilities for developers, providers, importers, and distributors. Only providers of high-risk systems are obligated to register their systems in the EU AI Database." Distributors focus onverification and communication, not formal registration.

NEW QUESTION # 78
Which of the following use cases would be best served by a non-AI solution?

A. An e-commerce provider wants to make personalized recommendations.
B. A customer service agency wants to automate answers to common questions.
C. A non-profit wants to develop a social media presence.
D. A business analyst wants to develop advertising campaigns.

Answer: C

Explanation:
The correct answer is A because developing a social media presence typically does not require AI and can be effectively achieved through traditional digital marketing strategies, content planning, and manual engagement. AI governance principles emphasize that organizations should first determine whether AI is necessary or proportionate to the problem being solved. Using AI where simpler, deterministic, or human-driven solutions suffice can introduce unnecessary complexity, cost, and risk. In contrast, options B, C, and D involve tasks such as campaign optimization, personalization, and automation, which benefit significantly from AI capabilities like pattern recognition, predictive analytics, and natural language processing. Responsible AI governance encourages a "fit-for-purpose" approach, ensuring AI is only deployed when it provides clear added value over non-AI alternatives.

NEW QUESTION # 79
According to the EU AI Act, providers of what kind of machine learning systems will be required to register with an EU oversight agency before placing their systems in the EU market?

A. AI systems that are harmful based on a legal risk-utility calculations.
B. AI systems that are "strong" general intelligence.
C. AI systems that are high-risk.
D. AI systems trained on sensitive personal data.

Answer: C

Explanation:
The EU AI Act classifies AI systems into four risk categories:
1. Unacceptable risk: AI applications posing a clear threat to safety, livelihoods, and rights of people, such as social scoring or real-time biometric identification in public spaces.
2. High-risk: AI systems that significantly impact health, safety, or fundamental rights, including those used in critical infrastructure, education, employment, and law enforcement.
3. Limited risk: AI systems with specific transparency obligations, like chatbots.
4. Minimal risk: AI systems with minimal regulatory requirements, such as spam filters.
Providers of high-risk AI systems must ensure compliance with the Act's requirements, including conducting a conformity assessment and registering the system in the EU database.

NEW QUESTION # 80
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