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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Trustworthiness, Ethical and Societal Implications - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases - AI Regulatory Compliance and Legal Considerations - AI Policies, Procedures, and Organizational Training |
| AI Risk Program Management | 42% | - AI Risk Response and Mitigation - AI Risk Monitoring and Reporting - AI Risk Assurance and Continuous Improvement - AI Risk Identification and Assessment |
| AI Life Cycle Risk Management | 21% | - AI Implementation, Maintenance, and Decommissioning - AI Design, Development/Procurement, and Documentation - AI Model Training, Testing, and Validation - AI Data and Asset Management |
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NEW QUESTION # 25
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?
Answer: D
NEW QUESTION # 26
Which of the following is MOST important to mitigate risk when integrating third-party AI services into an organization's supply chain?
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. Third-party AI integration requires enforceable allocation of responsibility. Contractual accountability for AI controls clarifies which party must implement, maintain, monitor, and remediate controls across the supplier relationship. This makes option A, Assigning contractual accountability for AI controls, 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 # 27
An organization seeks to implement a new AI system that uses customer information to create targeted product recommendations. Which of the following is the MOST important consideration to ensure the system complies with regulatory requirements?
Answer: B
Explanation:
Privacy and data protection regulations worldwide-including GDPR, CCPA, and sector-specific laws- impose strict requirements on the collection, use, and processing of personal information. Customer data used for AI systems must be obtained through lawful means with appropriate consent for the specific processing purpose.
Why A is Correct: According to ISACA AAIR guidance on regulatory compliance, the legal basis for processing personal data is the foundational requirement. An AI system built on data collected without proper consent or legal authorization exposes the organization to regulatory penalties, reputational damage, and forced shutdown of the system. Consent must be specific to the AI use case, not merely generic data collection consent.
Why B is Wrong: Backup and storage protocols address data security and resilience, which are compliance requirements but secondary to the lawfulness of data collection. Securely storing improperly obtained data does not cure the regulatory violation.
Why C is Wrong: Human review of recommendations is a governance safeguard for accuracy and fairness, not a regulatory compliance requirement for data collection. Many regulations do not require human review of recommendation systems.
Why D is Wrong: Supervised learning is a modeling technique that does not address regulatory compliance regarding data sourcing. The training methodology is irrelevant to whether the underlying data was legally obtained.
NEW QUESTION # 28
The MOST important consideration when reviewing existing business processes to determine their suitability for AI integration is whether:
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. Business processes are most suitable for AI integration when objectives, decisions, and rules are sufficiently defined for the AI tool to operate against clear requirements. Industry popularity, immediate scaling, and staffing reductions do not establish suitability. This makes option D, the process includes clearly defined rules for AI tools to follow, 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 # 29
Which of the following is the MOST important consideration when assessing risk for an AI system provided by a third party, as opposed to a non-AI related 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. Third-party AI requires greater continuous monitoring because models, data, dependencies, and provider behavior can change over time. Traditional onboarding assessments alone may not detect drift, updates, or newly introduced AI-specific risk. This makes option C, Greater emphasis on continuous monitoring due to the dynamically evolving nature of AI models, 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 # 30
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