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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Governance and Framework Integration | 37% | - AI Models, Frameworks, Strategies, and Use Cases - AI Organizational Processes and Alignment - AI Ownership, Oversight, and Accountability |
| AI Life Cycle Risk Management | - AI development, deployment, and monitoring risks - AI bias, drift, transparency, and control evaluation - AI model and data risk identification | |
| AI Risk Program Management | 42% | - AI risk monitoring and continuous improvement - Enterprise AI risk program design - AI risk assessment and treatment strategies - AI governance communication and reporting |
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NEW QUESTION # 38
Which of the following is the GREATEST organizational risk when privacy, cybersecurity, and legal teams are not integrated into the AI oversight committee?
Answer: C
Explanation:
Within the ISACA Advanced in AI Risk framework, governance decisions should align AI use with policy, accountability, stakeholder expectations, risk appetite, and applicable legal or ethical obligations. When privacy, cybersecurity, and legal functions are absent from integrated oversight, responsibilities can fall between organizational silos. The greatest risk is unclear accountability for control ownership, implementation, escalation, and remediation. This makes option D, Unclear accountability for AI control implementation, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk-management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
NEW QUESTION # 39
Which of the following is the GREATEST concern when an organization cannot clearly explain an AI system's decision-making process and the origin of its inputs?
Answer: C
Explanation:
Explainability and input transparency are foundational requirements for responsible AI governance. When these are absent, organizations lose the ability to identify when AI systems produce harmful, biased, or inaccurate results-leaving those harms undetected and unaddressed.
Why C is Correct: According to ISACA AAIR, the inability to explain AI decisions is most dangerous because it creates an environment where discriminatory or inaccurate outputs can persist undetected. This exposes the organization to regulatory penalties (particularly under anti-discrimination, financial services, and privacy laws), reputational damage, and harm to affected individuals. The detection gap-not knowing what the system is doing wrong-is the core governance failure.
Why A is Wrong: External provider dependence is a third-party risk management concern. While relevant, it is a structural risk that can be addressed through contract management, not an immediate consequence of lacking explainability.
Why B is Wrong: Declining adoption rates represent a change management and trust concern. Business unit reluctance to adopt AI is a cultural and operational issue, not the primary risk from unexplainable AI decisions.
Why D is Wrong: Manual review bottlenecks represent operational inefficiency. They may result from lack of confidence in AI outputs but do not represent the primary organizational harm from unexplainability.
NEW QUESTION # 40
Which of the following is the MOST important consideration when determining mitigation controls for an AI system?
Answer: D
Explanation:
Control selection for AI systems requires balancing the effectiveness and cost of proposed controls against the potential losses or harms the controls are designed to prevent. This cost-benefit analysis ensures resources are allocated proportionately to risk reduction value.
Why C is Correct: The ISACA AAIR control selection guidance identifies the cost-benefit analysis of control effectiveness versus potential business losses as the most important mitigation control determination factor.
Implementing controls that cost more than the risk they mitigate represents inefficient risk management; failing to implement cost-effective controls that prevent large losses represents inadequate risk management.
This proportionality assessment is the foundation of risk-based control selection.
Why A is Wrong: Risk awareness training is an important enabler of effective risk management but is an organizational capability development activity rather than a control selection criterion. Training supports controls but does not determine which controls to implement.
Why B is Wrong: Control performance baselines and compliance reporting requirements are governance and compliance management activities. While necessary for control monitoring, they describe how controls are measured after selection, not how controls are selected in the first place.
Why D is Wrong: Computational complexity is a technical characteristic of the AI system that influences implementation considerations but is not the primary driver of control selection. The most computationally complex system still requires controls proportionate to its risk profile, not its technical architecture.
NEW QUESTION # 41
A risk practitioner learns that a credit-scoring AI system is exhibiting bias that cannot be eliminated through further training. Which of the following is the risk practitioner ' s BEST recommendation?
Answer: B
NEW QUESTION # 42
An organization formally accepts residual risk for a low-impact AI capability after confirming it falls within the enterprise risk tolerance.
What is the primary benefit of this risk acceptance action?
Answer: C
Explanation:
Within the ISACA Advanced in AI Risk framework, program management connects risk identification, control selection, treatment, monitoring, resilience, third-party oversight, and reporting to enterprise risk objectives. When residual risk is within tolerance and affects non-critical functions, formal acceptance is proportionate and allows scarce mitigation resources to be directed toward higher-impact exposures.
Acceptance must still be documented and monitored rather than treated as inaction. This makes option A, It enables the allocation of mitigation resources to more critical AI-specific issues, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk-management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
NEW QUESTION # 43
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