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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Life Cycle Risk Management | 21% | - AI Design, Development/Procurement, and Documentation - AI Implementation, Maintenance, and Decommissioning - AI Data and Asset Management - AI Model Training, Testing, and Validation |
| Topic 2: AI Risk Governance and Framework Integration | 37% | - AI Models, Frameworks, Strategies, and Use Cases - AI Trustworthiness, Ethical and Societal Implications - AI Policies, Procedures, and Organizational Training - AI Ownership, Oversight, and Accountability - AI Regulatory Compliance and Legal Considerations - AI Organizational Processes and Alignment |
| Topic 3: AI Risk Program Management | 42% | - AI Risk Assurance and Continuous Improvement - AI Risk Response and Mitigation - AI Risk Identification and Assessment - AI Risk Monitoring and Reporting |
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NEW QUESTION # 138
Which of the following is MOST likely to be found in a risk mitigation plan for AI systems?
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. A risk mitigation plan should contain concrete measures that reduce identified AI risks, such as controls for data poisoning and algorithmic bias. Strategic objectives and vendor-selection criteria are governance inputs, not the actual treatment measures for the identified risk. This makes option C, Measures to address issues such as data poisoning and algorithmic bias, 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 # 139
Which of the following is the MOST important vendor assurance measure when an organization plans to engage multiple AI vendors for critical model components?
Answer: A
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 multiple vendors provide critical model components, assurance depends on evidence of provenance and integrity so the organization can trace the origin and handling of data and artifacts. Tool mandates or centralized IT ownership do not establish trustworthiness. This makes option A, Verifying documentation of data provenance and integrity, 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 # 140
An organization has developed an AI code of conduct outlining ethical use, data privacy, and transparency principles. Which of the following is the BEST approach to integrate the code of conduct into workforce training?
Answer: D
Explanation:
Effective ethics training must be relevant to the specific roles and responsibilities of each workforce segment, and must be reinforced over time as AI applications and ethical challenges evolve. Generic, one-time training produces shallow compliance rather than genuine ethical competence.
Why C is Correct: The ISACA AAIR Study Guide emphasizes role-tailored, continuous education as the best approach for embedding ethical principles into workforce behavior. Different roles-developers, business users, risk practitioners, executives-interact with AI in fundamentally different ways and face different ethical challenges. Tailored content ensures relevance, while scheduled refreshers maintain awareness as the ethical landscape changes with new AI deployments and regulatory developments.
Why A is Wrong: Onboarding incorporation is a starting point but insufficient alone. Ethics are not learned once at hire-they must be continuously reinforced as employees encounter new AI applications and ethical dilemmas in practice.
Why B is Wrong: External providers can deliver quality content but may not understand the organization's specific AI applications, culture, or risk profile. External delivery also tends to be episodic rather than integrated into ongoing role responsibilities.
Why D is Wrong: Focusing on legal compliance creates a rule-following culture rather than genuine ethical judgment. Compliance knowledge is necessary but insufficient for building the ethical reasoning skills needed for novel AI situations not covered by existing regulations.
NEW QUESTION # 141
Which of the following is the PRIMARY benefit of adopting an AI governance framework?
Answer: C
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. An AI governance framework primarily creates structured enterprise oversight, accountability, policy alignment, monitoring, and compliance. Resource allocation and technical standardization may improve, but they are secondary outcomes rather than the central governance benefit. This makes option A, Structured enterprise AI risk oversight and compliance, 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 # 142
Which of the following is the MOST important consideration when developing AI security policies?
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. 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.
NEW QUESTION # 143
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