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| Section | Objectives |
|---|---|
| AI Risk Management | - Risk identification and assessment for AI systems
|
| Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
| AI Lifecycle Controls | - Controls across AI development lifecycle
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| AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
| Regulatory and Compliance Requirements | - Global AI regulatory landscape
|
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NEW QUESTION # 179
A risk practitioner is performing a risk assessment of an AI system that will be used to predict failures in aircraft components. Which of the following is the MOST important design consideration in this context?
Answer: A
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. Aircraft- component failure prediction is safety-critical, so robust safety validation must demonstrate acceptable behavior, limitations, and failure modes before reliance. Integration, sensor capacity, and maintenance history support performance but do not replace safety assurance. This makes option C, Robust safety validation mechanisms, 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 # 180
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: A
Explanation:
Even when an AI system is initially assessed as within risk tolerance, its risk profile evolves as the system encounters new data, the operational environment changes, and model performance drifts. Controls that were effective at deployment may become insufficient as these changes accumulate.
Why C is Correct: The ISACA AAIR operational monitoring guidance identifies continuous monitoring for data and performance drift as the most important mechanism for maintaining control effectiveness over time.
Drift detection provides early warning when the AI system begins behaving differently from its validated state-enabling timely control adjustments before risk tolerance is breached. This is particularly critical because AI systems can degrade gradually in ways not visible without active monitoring.
Why A is Wrong: Framework alignment establishes the control baseline but does not actively verify that controls remain effective as the system evolves. Frameworks provide structure; monitoring provides assurance.
Why B is Wrong: Security and risk awareness training is an important human capability development activity but does not detect technical changes in AI system behavior. Training does not substitute for technical monitoring.
Why D is Wrong: Periodic compliance reviews occur at scheduled intervals and may miss drift that develops between review cycles. Continuous monitoring provides real-time detection that periodic reviews cannot match.
NEW QUESTION # 181
Which of the following is MOST important when defining responsible roles for integrating third-party AI services into an organization's supply chain?
Answer: B
Explanation:
Third-party AI service integration introduces distributed accountability challenges. When external services are incorporated into organizational supply chains, clearly designated ownership of AI governance and risk is essential to ensure responsibilities do not fall into gaps between internal and external parties.
Why A is Correct: According to ISACA AAIR third-party risk principles, designating AI governance and risk ownership is the foundational requirement for supply chain integration. Without clear internal ownership, third-party AI risks cannot be effectively monitored, escalated, or managed. The designated owner ensures vendor performance is assessed against risk criteria, contractual obligations are enforced, and emerging risks are addressed.
Why B is Wrong: Standardizing data transfer protocols is a technical integration concern. While important for security and operations, it does not address who is responsible for managing the ongoing governance and risk of the integrated service.
Why C is Wrong: Training third-party staff on internal AI policies is a vendor management activity that may be contractually required but does not substitute for internal governance ownership. Third-party training does not remove the organization's responsibility for oversight.
Why D is Wrong: Security policy alignment is important for consistent security posture but represents one dimension of third-party risk management. Governance and risk ownership encompasses security policy alignment as well as broader risk management responsibilities.
NEW QUESTION # 182
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 # 183
Which of the following is the MOST important reason for a risk practitioner to classify AI risk using threat actor profiles?
Answer: B
Explanation:
Threat actor profiling characterizes the motivations, capabilities, and likely attack methods of potential adversaries. In AI risk management, understanding who the likely attackers are and what they seek enables the design of controls specifically matched to the actual threat landscape.
Why B is Correct: According to ISACA AAIR threat-based risk management guidance, the most important reason for threat actor profiling is to tailor controls to adversary motivations and capabilities. Different threat actors-nation-state attackers, criminal organizations, competitors, insiders, activists-have different objectives (espionage vs. financial gain vs. disruption), capabilities (sophisticated vs. opportunistic), and methods. Controls calibrated to actual threat actor profiles are significantly more effective than generic controls that may not address the specific threats the organization actually faces.
Why A is Wrong: Aligning AI threats with IT control taxonomy is a governance integration activity that improves control consistency but does not capture the threat actor-specific tailoring value of profiling.
Taxonomy alignment is an administrative benefit; threat-tailored controls are a security effectiveness benefit.
Why C is Wrong: Response metrics for cybersecurity incidents are developed for incident management planning. Threat actor profiling informs control design and incident response strategies but is not primarily used to develop response metrics.
Why D is Wrong: Prioritizing external threats over internal threats is a security strategy choice that threat actor profiling does not prescribe. Many AI attacks, including insider threats and social engineering, are internal. Profiling should result in appropriate prioritization based on actual threat likelihood, not a blanket prioritization of external threats.
NEW QUESTION # 184
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