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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases |
| Topic 2: AI Life Cycle Risk Management | - AI bias, drift, transparency, and control evaluation - AI development, deployment, and monitoring risks - AI model and data risk identification | |
| Topic 3: AI Risk Program Management | 42% | - Enterprise AI risk program design - AI risk assessment and treatment strategies - AI risk monitoring and continuous improvement - AI governance communication and reporting |
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NEW QUESTION # 46
A risk practitioner discovers that an AI chatbot stores user interactions indefinitely. Which of the following is the MOST appropriate mitigation?
Answer: B
Explanation:
Within the ISACA Advanced in AI Risk framework, life-cycle controls should protect data quality, model design, testing, validation, monitoring, change management, and secure retirement of AI systems. Indefinite chatbot retention creates unnecessary privacy and breach exposure. Automated retention limits linked to documented consent or purpose ensure records are kept only as long as justified while still accommodating legitimate legal, operational, or audit requirements. This makes option B, Automate retention limits linked to documented consent, 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 # 47
Which of the following is the GREATEST risk when AI governance fails to incorporate stakeholder perspectives in policy and design decisions?
Answer: A
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. Excluding stakeholder perspectives can produce AI behavior and outputs that do not match the intended business case, affected-user needs, or acceptable values. Governance must incorporate those perspectives so technical success does not become business or societal misalignment. This makes option A, Misalignment of AI behavior and outputs with expected business cases, 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 # 48
A risk practitioner is concerned that an AI model's responses have become more inaccurate over time, leading to diminished customer trust. Which of the following should the risk practitioner recommend be done FIRST?
Answer: B
Explanation:
Incident response for AI model degradation should follow a structured diagnostic process. Before implementing any corrective action, the scope and nature of the accuracy issues must be understood to ensure the response is appropriate and targeted.
Why D is Correct: According to ISACA AAIR incident response guidance, the first step when AI model accuracy deteriorates is to assess the impact-understanding which specific features are affected, how model outputs have changed, and what the business consequences are. This diagnostic step informs all subsequent decisions about whether to retrain, add validation cycles, or take the system offline. Acting without this assessment may waste resources on inappropriate responses or leave critical issues unaddressed.
Why A is Wrong: Adding validation review cycles is a process change that may be appropriate but cannot be determined without first understanding the nature and scope of the accuracy problem. Reviews address a symptom without diagnosing the cause.
Why B is Wrong: Taking the model offline and backing it up is a drastic operational measure that may be disproportionate to the actual issue. This decision requires understanding the severity and scope of the problem, which requires impact assessment first.
Why C is Wrong: Full model retraining is resource-intensive and may not address the root cause if the problem is not training data staleness. Impact assessment must precede the decision to retrain.
NEW QUESTION # 49
Which of the following is the MOST appropriate key performance indicator (KPI) for the effectiveness of a targeted AI risk awareness training program?
Answer: B
Explanation:
Training program effectiveness KPIs must measure behavioral change-whether training has actually altered how participants act in their work environment-rather than knowledge acquisition or adoption rates. The most meaningful behavioral signal for AI risk awareness training is whether trained users report suspicious activity.
Why B is Correct: According to ISACA AAIR training effectiveness measurement guidance, the number of AI irregularities and potential tampering incidents reported by users is the most appropriate behavioral KPI for risk awareness training effectiveness. When users report unusual AI behavior, this demonstrates they have internalized training concepts well enough to recognize anomalies and understand their obligation to report them. This behavioral change-from passive observation to active reporting-is the intended outcome of awareness training.
Why A is Wrong: Risk rating changes measure risk management process adjustments rather than individual behavioral change from training. Risk ratings reflect aggregate organizational risk, not the specific behavioral impact of an awareness training program.
Why C is Wrong: Ability to identify financial impacts is a knowledge assessment metric-it measures what users know rather than what they do differently as a result of training. Awareness training aims to change behavior, not just inform.
Why D is Wrong: AI adoption rates measure technology uptake, not risk awareness. Higher adoption could indicate confidence in AI systems but does not measure whether employees recognize and report AI risks- the specific objective of risk awareness training.
NEW QUESTION # 50
A risk practitioner assesses a new AI system and determines that the risk is within the organization ' s risk tolerance. Which of the following is the BEST recommendation to ensure system controls remain effective over time?
Answer: D
NEW QUESTION # 51
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