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| Section | Objectives |
|---|---|
| AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
| AI Lifecycle Controls | - Controls across AI development lifecycle
|
| Regulatory and Compliance Requirements | - Global AI regulatory landscape
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| AI Risk Management | - Risk identification and assessment for AI systems
|
| Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
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NEW QUESTION # 30
Which of the following should be a risk practitioner's PRIMARY consideration when developing risk scenarios related to adversarial manipulation of a business-critical AI system?
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. Risk scenarios for adversarial manipulation should be classified using criteria aligned with organizational tolerance so likelihood and impact can drive proportionate treatment decisions. Attack prevalence and patch frequency are inputs, not the governing risk criterion. This makes option C, Alignment of risk classification criteria with organizational tolerance, 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 # 31
An organization seeks to improve AI oversight by incorporating external perspectives regarding potential public harms from AI use. Which of the following is MOST important to consider?
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. External perspectives are best incorporated through formal procedures for engaging affected communities and independent experts. Metrics and post-deployment complaints are useful, but they do not substitute for direct stakeholder participation when assessing public or societal harms. This makes option A, Formal procedures to solicit and prioritize feedback from affected communities and independent experts, 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 # 32
An organization intends to implement an AI system that poses significant societal risk and interfaces with critical infrastructure and public services. Which of the following is the BEST course of action?
Answer: A
Explanation:
High-risk AI systems-particularly those affecting critical infrastructure and public services-require rigorous pre-deployment assessment to identify potential harms, regulatory obligations, and societal impacts before they affect people or essential services.
Why A is Correct: The ISACA AAIR framework, consistent with emerging AI regulations (including the EU AI Act's requirements for high-risk systems), mandates comprehensive pre-launch impact assessment for systems posing significant societal risk. This assessment must cover adverse impact scenarios, applicable compliance obligations, and mitigation measures. Acting before deployment prevents irreversible harm and demonstrates responsible governance to regulators and the public.
Why B is Wrong: External consultants can support impact assessment but cannot substitute for the organization's own comprehensive evaluation and accountability. External expertise supplements internal assessment; it does not replace the organization's obligation to assess and take responsibility.
Why C is Wrong: Restricting disclosure conflicts with regulatory transparency requirements for high-risk AI systems. Many jurisdictions require explainability and disclosure for systems affecting public services. IP protection cannot override public safety obligations.
Why D is Wrong: Parallel model evaluation is a technical testing method that quantifies operational performance. It does not constitute the comprehensive societal impact and compliance assessment required for high-risk deployment.
NEW QUESTION # 33
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 # 34
Which of the following is the MOST significant risk when an organization depends on a single AI vendor ' s proprietary environment?
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. Dependence on a single proprietary AI environment can create vendor lock-in, making migration technically difficult, operationally disruptive, and expensive. Transparency and scalability are relevant concerns, but prohibitive switching costs are the central dependency risk. This makes option B, Prohibitive migration costs, 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 # 35
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