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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Program Management | 42% | - AI risk assessment and treatment strategies - AI governance communication and reporting - AI risk monitoring and continuous improvement - Enterprise AI risk program design |
| AI Life Cycle Risk Management | - AI model and data risk identification - AI development, deployment, and monitoring risks - AI bias, drift, transparency, and control evaluation | |
| AI Risk Governance and Framework Integration | 37% | - AI Organizational Processes and Alignment - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases |
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NEW QUESTION # 96
An organization depends on multiple external suppliers for AI models and training datasets. Which of the following is MOST important to have in place in order to reduce supply chain risk?
Answer: D
Explanation:
AI supply chain risk arises when external models or datasets are tampered with, have undisclosed characteristics, or cannot be traced to trusted origins. End-to-end provenance and audit trails address these risks by enabling verification of integrity and origin at every stage of the supply chain.
Why A is Correct: According to ISACA AAIR supply chain risk management guidance, verifiable provenance and audit trails are the most important supply chain protection mechanism. Provenance documentation traces the origin, handling, and transformation history of every externally sourced AI artifact- enabling the organization to verify that models and datasets have not been tampered with, that data sources are legitimate, and that the supply chain has not been compromised. Without provenance, organizations cannot distinguish trustworthy from compromised artifacts.
Why B is Wrong: Indemnity clauses assign financial liability after harm occurs. They provide legal recourse but do not prevent supply chain attacks or help the organization verify artifact integrity before deployment.
Why C is Wrong: Training method documentation provides useful technical context but does not verify that the actual artifacts delivered match the documentation. Documentation can be falsified; provenance verification with cryptographic integrity checks cannot.
Why D is Wrong: A vendor risk manager provides governance oversight and relationship management. While important for managing vendor relationships, a single contact point does not substitute for technical provenance verification of every artifact in the supply chain.
NEW QUESTION # 97
Which of the following BEST enables an organization to comply with regulations on the use of biometric data by its AI models?
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. Biometric compliance requires governance over purpose, consent, access, retention, and authorized use. Liveness detection and vulnerability scanning improve security, but purpose-based governance is what prevents sensitive biometric data from being repurposed beyond approved uses. This makes option D, Implementing strong governance to ensure biometric data is used only for its intended purposes, 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 # 98
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: D
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 # 99
Which of the following is the BEST risk response when an organization identifies that ethical and legal exposures from a new non-critical AI system exceeds its risk tolerance?
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. When ethical and legal exposures exceed tolerance and the AI system is non-critical, avoidance is the most proportionate response. Acceptance is inappropriate above tolerance, transfer cannot remove all accountability, and mitigation is suitable only if effective controls can reduce exposure sufficiently. This makes option D, Avoidance, 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 # 100
Which of the following BEST supports the explainability and transparency of AI model deployments?
Answer: B
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.
Explainability depends on traceability. Documentation of model logic and data provenance provides evidence of how outputs were produced and which data influenced them, supporting auditability, accountability, and meaningful review of AI decisions. This makes option D, Documentation of model logic and data provenance, 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 pre serving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
NEW QUESTION # 101
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