IAPP Updated AIGP Exam Questions and Answers by rohan

The correct answer is D because one of the most significant risks associated with generative AI is the potential leakage of sensitive, confidential, or proprietary information. AI governance frameworks emphasize data protection, confidentiality, and secure data handling as critical organizational responsibilities. When employees input sensitive data into generative AI tools, especially external or third-party systems, that information may be stored, reused, or exposed unintentionally. This creates legal, regulatory, and reputational risks. As a result, organizations may restrict or prohibit generative AI use to prevent unauthorized data disclosure. The other options relate to operational or business considerations, which are not primary governance drivers. Protecting sensitive information aligns with core AI governance principles such as privacy, security, and risk mitigation, making it the strongest justification for such a policy.

The correct answer is Explainable Ai because it specifically refers to the ability of a system to describe the logic behind its decisions or output in a way that is understandable to humans. This is a key part of regulatory and ethical frameworks and is directly related to addressing the black-box problem in AI.

From the AIGP ILT Participant Guide (Module on Transparency and Explainability):

“Explainability refers to the understanding of how a black-box model works. The black-box problem exists because some models are too complex for human interpretation. Explainability methods aim to provide meaningful insight into the logic and decision-making of AI systems.”

Also, according to the AI Governance in Practice Report 2025:

“Explainability refers to the representation of the underlying mechanisms of the AI system’s operation... a key tenet of AI governance due to the desire to understand how AI systems are built, managed and maintained.”

Thus, while Trustworthy and Responsible AI are broader concepts,explainabilityspecifically targets the regulatory concern about understanding outputs.

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Under theEU AI Act, serious incidents involvinghigh-risk AI systemsmust be reported. The deployer is required topromptly inform the provider and relevant authoritiesabout the issue.

From theAI Governance in Practice Report 2025:

“Serious incidents involving high-risk systems… must be reported to the provider and relevant market surveillance authority.” (p. 35)

“Timely reporting is required when AI systems result in or may result in violations of fundamental rights.” (p. 35)

The planning phase of the AI life cycle typically includes defining the objective of the model, choosing the appropriate architecture, and understanding the context in which the model will operate. However, the approach to governance is usually established as part of the overall AI governance framework, not specifically within the planning phase. Governance encompasses broader organizational policies and procedures that ensure AI development and deployment align with legal, ethical, and operational standards. Reference: AIGP Body of Knowledge, AI lifecycle planning phase section.