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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases |
| AI Life Cycle Risk Management | - AI development, deployment, and monitoring risks - AI model and data risk identification - AI bias, drift, transparency, and control evaluation | |
| AI Risk Program Management | 42% | - AI governance communication and reporting - AI risk monitoring and continuous improvement - Enterprise AI risk program design - AI risk assessment and treatment strategies |
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51. Frage
Which of the following is the GREATEST concern when AI risk management operates separately from enterprise risk management (ERM)?
Antwort: C
Begründung:
Enterprise Risk Management (ERM) provides the strategic framework within which all organizational risks- including AI risks-should be managed. When AI risk management operates in isolation, it loses connection to enterprise strategy, risk appetite, and cross-functional control objectives.
Why A is Correct: The ISACA AAIR curriculum identifies strategic control alignment as a foundational ERM integration requirement. When AI risk operates independently, controls may conflict with or duplicate enterprise controls, risk appetite thresholds may differ, and AI risks cannot be aggregated or prioritized alongside other organizational risks. This misalignment creates blind spots at the enterprise level and undermines coherent strategic risk management.
Why B is Wrong: Inconsistent regulatory reporting is a compliance concern but is a downstream consequence of poor governance rather than the greatest organizational risk from separation. Regulatory gaps can often be patched operationally without full integration.
Why C is Wrong: Training cost increases represent a financial efficiency concern unrelated to the governance challenge of separate risk management functions. ROI impacts are not driven by organizational structure of risk management.
Why D is Wrong: Redundant documentation is an operational inefficiency, not a strategic risk. Duplicated records are wasteful but do not threaten organizational strategy or expose the enterprise to unmanaged risk.
52. Frage
Which of the following is the BEST justification for selecting a risk avoidance strategy when considering whether to deploy a high-impact AI system?
Antwort: A
Begründung:
Risk avoidance is the risk treatment strategy of not engaging in an activity because the risks it presents cannot be adequately mitigated to within acceptable tolerance. For high-impact AI systems, the justification for avoidance must be proportionate to the gravity of the decision to forgo deployment entirely.
Why A is Correct: The ISACA AAIR risk treatment framework identifies potential harm to stakeholders as the most compelling justification for risk avoidance in AI deployment decisions. When a high-impact AI system poses risks of significant harm to individuals, communities, or society that cannot be adequately controlled, avoiding deployment is the ethically and legally appropriate choice. Stakeholder harm-especially irreversible or widespread harm-represents the highest severity risk outcome and justifies the most conservative risk treatment.
Why B is Wrong: Cost reduction objectives are business case considerations, not risk management justifications. Avoiding deployment to reduce costs is a financial decision, not a risk avoidance strategy. Risk avoidance decisions are driven by harm potential, not cost efficiency.
Why C is Wrong: Staff expertise shortages represent an organizational capability constraint that can be addressed through hiring, training, or managed services. A capability gap is a surmountable operational challenge, not a justification for permanently avoiding a valuable deployment.
Why D is Wrong: Data poisoning attack likelihood is a security risk that can be mitigated through appropriate controls-data integrity verification, provenance tracking, anomaly detection. A manageable risk with available mitigations does not justify full risk avoidance when stakeholder harm is not at stake.
53. Frage
A conversational AI accepts unrestricted user text and can be coerced into disclosing secrets or taking harmful actions. Which control MOST effectively reduces this risk?
Antwort: B
Begründung:
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. A conversational system exposed to unrestricted text is vulnerable to prompt injection and unsafe output. Runtime input validation and output filtering directly constrain malicious instructions and help prevent disclosure of secrets or harmful actions. This makes option D, Implement runtime input validation and output filtering, 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.
54. Frage
Which of the following is the MOST important consideration to reduce risk during the development of a large language model (LLM)?
Antwort: D
Begründung:
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. Security should be assessed throughout LLM design, development, testing, deployment, and maintenance so vulnerabilities and unsafe behaviors are identified before becoming embedded in production. Threat analysis and staff training are supporting activities within that broader secure lifecycle. This makes option D, Ensuring security is assessed throughout the development life cycle, 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.
55. Frage
Which of the following should be the PRIMARY consideration when determining the priority for restoration of AI systems following a model exfiltration attack?
Antwort: C
Begründung:
Following a model exfiltration attack, multiple AI systems may require restoration. Prioritization must be based on objective criteria that reflect the potential business impact of continued unavailability. Systems supporting critical business functions must be restored before those supporting non-critical functions.
Why A is Correct: According to ISACA AAIR business continuity guidance for AI, the primary criterion for restoration priority is the AI system's criticality to business requirements. Systems that support mission- critical functions-patient care, financial transaction processing, safety operations-represent the highest restoration priority because their unavailability causes the greatest operational harm. This risk-based prioritization framework is consistent with standard business continuity management principles applied to the AI context.
Why B is Wrong: Team member expertise affects restoration capacity and speed but should not drive prioritization decisions. Priority is determined by business impact, not by where the team has the most technical capability. Resource allocation follows priority, not the reverse.
Why C is Wrong: Vulnerability testing and patch costs are operational considerations that may influence restoration timelines but should not override business criticality in determining priority. Cost-based prioritization could lead to restoring cheaper but less critical systems first.
Why D is Wrong: Dataset availability affects the feasibility and timeline of model retraining but is a logistical consideration rather than the primary basis for restoration priority. Critical systems should be prioritized even if their restoration is technically more complex.
56. Frage
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