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| Section | Weight | Objectives |
|---|---|---|
| AI Life Cycle Risk Management | - AI bias, drift, transparency, and control evaluation - AI model and data risk identification - AI development, deployment, and monitoring risks | |
| AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases - AI Organizational Processes and Alignment |
| AI Risk Program Management | 42% | - AI governance communication and reporting - AI risk assessment and treatment strategies - Enterprise AI risk program design - AI risk monitoring and continuous improvement |
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15. Frage
Which of the following approaches is MOST effective for embedding management of AI risk into existing organizational processes and decision-making?
Antwort: C
Begründung:
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.
16. Frage
Which of the following is the MOST important reason to include AI-specific risk and compliance clauses in vendor contracts?
Antwort: A
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. AI-specific contract clauses should clearly allocate liability and responsibilities for breaches affecting models, data, and services. Baseline frameworks and anonymization duties may be included, but enforceable accountability is the key reason for risk-based contracting. This makes option A, Assignment of liability for breaches impacting models and training data, 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.
17. Frage
A risk practitioner assesses an AI model used for predictive diagnostics and finds that the system lacks automated update mechanisms. Which of the following is the GREATEST risk?
Antwort: C
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. A predictive diagnostic model that cannot update may continue using assumptions that no longer reflect current conditions, compromising accuracy as the environment changes. Human effort is secondary to the risk of incorrect predictions based on stale relationships. This makes option D, Compromise of predictive accuracy due to outdated model assumptions, 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.
18. Frage
An organization deploys an autonomous system that makes decisions affecting compliance with regulations.
If those decisions could potentially produce regulatory breaches, which of the following BEST helps to manage associated liability exposures?
Antwort: A
Begründung:
Liability from autonomous AI decisions affecting regulatory compliance requires organizations to demonstrate accountability, oversight, and control. Documentation of decision rationale and embedded oversight controls are the primary mechanisms for demonstrating responsible governance to regulators.
Why B is Correct: The ISACA AAIR framework identifies explainability documentation and embedded oversight controls as the key liability management tools for autonomous AI systems. When the organization can demonstrate that each AI decision was explainable, that controls were in place to detect violations, and that human oversight was embedded in the process, this demonstrates due diligence-which is the legal and regulatory standard for managing liability from automated decisions.
Why A is Wrong: Separate compliance programs fragment governance and may increase rather than reduce liability by suggesting AI compliance is siloed from the enterprise compliance program. Regulators expect integrated governance.
Why C is Wrong: Restricting deployment represents risk avoidance, not liability management for already- deployed systems. If the system is already in production, deployment restriction does not address existing liability.
Why D is Wrong: Single-point escalation and non-disclosure create governance bottlenecks and conflict with regulatory transparency requirements. Restricting disclosure cannot be used to shield the organization from regulatory accountability for automated decisions.
19. Frage
Which of the following is the MOST important consideration when developing AI security policies?
Antwort: D
Begründung:
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.
20. Frage
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