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| Section | Weight | Objectives |
|---|---|---|
| AI Life Cycle Risk Management | - AI bias, drift, transparency, and control evaluation - AI development, deployment, and monitoring risks - AI model and data risk identification | |
| AI Risk Program Management | 42% | - AI risk monitoring and continuous improvement - AI governance communication and reporting - AI risk assessment and treatment strategies - Enterprise AI risk program design |
| AI Risk Governance and Framework Integration | 37% | - AI Models, Frameworks, Strategies, and Use Cases - AI Ownership, Oversight, and Accountability - AI Organizational Processes and Alignment |
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NEW QUESTION # 174
Which of the following is the MOST effective way to ensure identified AI risk is considered in business strategy decisions?
Answer: D
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. Mapping identified AI risks to organizational objectives translates technical exposure into business consequences and ensures risk is considered in strategic decisions. Workshops and vulnerability reports help identify issues but do not create the same direct strategy linkage. This makes option A, Map AI risk to organizational objectives, 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 # 175
Which of the following poses the GREATEST challenge when performing root cause analysis for incidents involving AI systems and data?
Answer: C
Explanation:
Root cause analysis for AI incidents requires the ability to trace system behavior back through decision logic, data processing steps, and model internals to identify what caused the incident. AI systems-particularly deep learning models-often operate as black boxes, making this tracing extremely difficult.
Why A is Correct: According to ISACA AAIR incident management guidance, the lack of transparency in AI systems is the greatest root cause analysis challenge. When decision logic cannot be inspected, when data lineage is unclear, or when model internals are opaque, analysts cannot determine why the system behaved as it did. This transparency deficit prevents accurate root cause identification, perpetuates recurrence, and makes it impossible to demonstrate corrective action to regulators.
Why B is Wrong: Unclear system objectives represent a design and governance problem that should be addressed before deployment. While unclear objectives can contribute to incidents, they are typically knowable and addressable. Lack of transparency during an incident is a more immediate analytical barrier.
Why C is Wrong: Automation bias-the tendency to over-trust automated systems-is a human factors risk that affects decision-making during normal operations. While it may contribute to incidents, it is a behavioral phenomenon rather than the primary technical barrier to root cause analysis.
Why D is Wrong: Privacy compliance requirements may restrict access to certain data needed for analysis, creating constraints on investigation. However, these are governance constraints that can often be addressed through appropriate authorization, not fundamental analytical barriers.
NEW QUESTION # 176
Which of the following is the MOST important consideration when developing AI security policies?
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. AI security policies should be relevant to the organization ' s current and planned use cases and strategic objectives. A policy disconnected from actual AI adoption will not establish useful requirements for the risks the organization is taking. This makes option B, Relevance to current and projected AI use cases and strategic objectives, 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 # 177
Which of the following is the BEST risk response when an organization identifies that ethical and legal exposures from a new non-critical AI system exceeds its risk tolerance?
Answer: A
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 ethical and legal exposures exceed tolerance and the AI system is non-critical, avoidance is the most proportionate response. Acceptance is inappropriate above tolerance, transfer cannot remove all accountability, and mitigation is suitable only if effective controls can reduce exposure sufficiently. This makes option D, Avoidance, 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 # 178
Which of the following approaches is MOST effective for embedding management of AI risk into existing organizational processes and decision-making?
Answer: B
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. AI risk is best embedded by integrating governance checkpoints into established project, change, and risk-review cycles. This ensures AI considerations are part of normal decision-making instead of being handled by a parallel process that can become isolated from business governance. This makes option B, Integrate AI governance into established project and risk review cycles, 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 # 179
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