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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases - AI Trustworthiness, Ethical and Societal Implications - AI Policies, Procedures, and Organizational Training - AI Regulatory Compliance and Legal Considerations - AI Organizational Processes and Alignment |
| AI Risk Program Management | 42% | - AI Risk Response and Mitigation - AI Risk Monitoring and Reporting - AI Risk Identification and Assessment - AI Risk Assurance and Continuous Improvement |
| AI Life Cycle Risk Management | 21% | - AI Data and Asset Management - AI Implementation, Maintenance, and Decommissioning - AI Model Training, Testing, and Validation - AI Design, Development/Procurement, and Documentation |
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NEW QUESTION # 114
In the context of AI risk mitigation, which of the following is the PRIMARY reason to have rollback capabilities in place for AI system updates?
Answer: D
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. Rollback capability allows the organization to restore a previously validated state when an AI update causes unintended consequences such as degraded accuracy, new bias, control failures, or unsafe behavior. It is a resilience and change-management safeguard. This makes option B, To correct unintended consequences, 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 # 115
Which of the following is the GREATEST risk when an organization relies only on adversarial training to protect a private AI model in a testing environment?
Answer: B
Explanation:
Adversarial training improves model robustness against known attack patterns by incorporating adversarial examples into the training process. However, no single security technique provides comprehensive protection-adversarial training addresses only the attack vectors it was designed for, leaving other vulnerabilities unaddressed.
Why B is Correct: The ISACA AAIR security defense-in-depth guidance identifies residual system vulnerabilities as the greatest risk when adversarial training is the sole security measure. Adversarial training protects against specific attack types (evasion, perturbation) but does not address infrastructure vulnerabilities, API security weaknesses, model inversion attacks, membership inference, or other security risks present in a testing environment. A defense-in-depth approach is required for comprehensive protection.
Why A is Wrong: Adversarial training does increase computational requirements and may extend training cycles, but inefficiency is an operational concern rather than a security risk. The security risk of unprotected vulnerabilities significantly outweighs training cycle efficiency.
Why C is Wrong: Overfitting to adversarial training examples is a model quality concern that can be managed through standard regularization techniques. It represents a model performance trade-off, not the greatest security risk from relying solely on adversarial training.
Why D is Wrong: Exposure of proprietary algorithms is an intellectual property risk that is not specifically increased by relying on adversarial training. Algorithm confidentiality is protected through access controls and encryption, which are separate from the adversarial training approach.
NEW QUESTION # 116
Which of the following poses the GREATEST challenge related to the protection of intellectual property generated by AI solutions?
Answer: B
Explanation:
Traditional intellectual property law was designed for human-created works. AI-generated content sits in a legal grey zone because current copyright frameworks in most jurisdictions do not clearly establish who-if anyone-holds copyright in outputs created autonomously by AI systems.
Why C is Correct: According to ISACA AAIR, the lack of regulatory clarity around AI-generated content copyright is the greatest IP challenge because it creates fundamental uncertainty about ownership, transferability, and enforceability of rights in AI outputs. Without clear legal status, organizations cannot confidently assert ownership, license AI-generated materials, or prevent competitors from copying outputs.
This uncertainty pervades commercial agreements, licensing strategies, and competitive protection.
Why A is Wrong: Zero-data retention policies actually protect intellectual property by ensuring vendor systems do not retain proprietary input data. This represents a protective measure, not a challenge.
Why B is Wrong: Training material customization for confidential data handling is a workforce education challenge. While important for data protection, it does not represent the primary IP challenge from AI- generated content.
Why D is Wrong: Low-risk use cases like administrative tasks present minimal IP concerns because the outputs are typically not commercially significant or protectable. The IP challenge is greatest for creative, analytical, and proprietary outputs.
NEW QUESTION # 117
An organization has identified a moderate AI exposure from potential model inaccuracies that could affect internal reporting. The risk falls within the organization's defined tolerance. Which of the following is the BEST course of action?
Answer: B
Explanation:
Risk treatment decisions must be proportionate to the risk level relative to organizational tolerance. When risk falls within defined tolerance, the appropriate treatment is formal acceptance with ongoing monitoring-not escalation of controls or system suspension that would be disproportionate to the risk level.
Why A is Correct: According to ISACA AAIR risk treatment guidance, when identified risk falls within the organization's tolerance threshold, the appropriate response is documented risk acceptance with continued monitoring against thresholds. This proportionate response preserves operational efficiency while maintaining oversight. Implementing controls beyond what the risk level warrants wastes resources and may introduce unnecessary operational disruption.
Why B is Wrong: Aggressively lowering model temperature changes model output characteristics and requires comprehensive retesting-a significant investment of resources. This disproportionate technical response is not warranted for risk that is already within tolerance.
Why C is Wrong: Allocating additional human review resources increases operational costs to manage a risk that the organization has determined is already acceptable. Additional controls beyond tolerance-appropriate levels represent unnecessary risk over-treatment.
Why D is Wrong: Taking the system offline for retraining is a drastic risk avoidance response appropriate only when risk exceeds tolerance or when an active harm is occurring. For risk within tolerance, system suspension is entirely disproportionate and unnecessary.
NEW QUESTION # 118
Which of the following is the MOST important reason that risk practitioners should distinguish among traditional supervised models, unsupervised models, and large language models (LLMs) when assessing AI risk?
Answer: D
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. Supervised, unsupervised, and large language models have different risk profiles for explainability, fairness, robustness, hallucination, data dependence, and validation. Distinguishing model types allows the risk assessment to select controls that match the actual technology. This makes option A, Each type of model has different explainability, fairness, and resiliency profiles, 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 # 119
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