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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Life Cycle Risk Management | 21% | - AI Implementation, Maintenance, and Decommissioning - AI Model Training, Testing, and Validation - AI Design, Development/Procurement, and Documentation - AI Data and Asset Management |
| Topic 2: AI Risk Program Management | 42% | - AI Risk Assurance and Continuous Improvement - AI Risk Monitoring and Reporting - AI Risk Identification and Assessment - AI Risk Response and Mitigation |
| Topic 3: AI Risk Governance and Framework Integration | 37% | - AI Regulatory Compliance and Legal Considerations - AI Policies, Procedures, and Organizational Training - AI Trustworthiness, Ethical and Societal Implications - AI Organizational Processes and Alignment - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases |
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NEW QUESTION # 78
Which of the following is the PRIMARY purpose of embedding human-centered values into AI governance frameworks?
Answer: D
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. Embedding human-centered values in AI governance is intended to reduce societal, safety, ethical, and environmental harms and protect the rights and interests of affected stakeholders. Transparency and organizational legitimacy are related benefits but are narrower outcomes. This makes option C, Mitigating societal and environmental risk, 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 # 79
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: C
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. 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.
NEW QUESTION # 80
An organization embeds AI into existing processes without integrating AI risk practices into enterprise governance. Which of the following should a risk practitioner regard as the GREATEST organizational risk?
Answer: C
Explanation:
When AI is deployed without governance integration, no formal structure exists to assign control ownership, coordinate risk management activities, or align AI decision-making with organizational objectives. This structural void produces divergent, fragmented, and potentially conflicting risk management efforts.
Why C is Correct: According to ISACA AAIR, unclear ownership is the greatest organizational risk from AI operating outside governance structures. Without designated owners, controls may be applied inconsistently across business units, different teams may implement conflicting approaches, and no one is responsible for ensuring AI activities align with enterprise objectives. This governance vacuum creates unmanaged risks and organizational incoherence.
Why A is Wrong: Regulatory compliance documentation gaps are significant but are a downstream symptom of poor governance rather than the root organizational risk. Documentation failures can be remediated more easily than fundamental ownership gaps.
Why B is Wrong: Technical-business alignment is an important concern but represents a strategic planning challenge rather than the greatest organizational risk from absent governance. Alignment can be achieved through business case processes without full governance integration.
Why D is Wrong: Executive approval difficulty is an organizational change management challenge. It reflects organizational politics rather than a structural risk from absent governance. Approval processes function independently of AI governance integration.
NEW QUESTION # 81
Which of the following is the MOST important reason to include AI-specific risk and compliance clauses in vendor contracts?
Answer: D
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. 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.
NEW QUESTION # 82
Which of the following is MOST important when defining responsible roles for integrating third-party AI services into an organization's supply chain?
Answer: C
Explanation:
Third-party AI service integration introduces distributed accountability challenges. When external services are incorporated into organizational supply chains, clearly designated ownership of AI governance and risk is essential to ensure responsibilities do not fall into gaps between internal and external parties.
Why A is Correct: According to ISACA AAIR third-party risk principles, designating AI governance and risk ownership is the foundational requirement for supply chain integration. Without clear internal ownership, third-party AI risks cannot be effectively monitored, escalated, or managed. The designated owner ensures vendor performance is assessed against risk criteria, contractual obligations are enforced, and emerging risks are addressed.
Why B is Wrong: Standardizing data transfer protocols is a technical integration concern. While important for security and operations, it does not address who is responsible for managing the ongoing governance and risk of the integrated service.
Why C is Wrong: Training third-party staff on internal AI policies is a vendor management activity that may be contractually required but does not substitute for internal governance ownership. Third-party training does not remove the organization's responsibility for oversight.
Why D is Wrong: Security policy alignment is important for consistent security posture but represents one dimension of third-party risk management. Governance and risk ownership encompasses security policy alignment as well as broader risk management responsibilities.
NEW QUESTION # 83
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