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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Program Management | 42% | - AI Risk Response and Mitigation - AI Risk Assurance and Continuous Improvement - AI Risk Identification and Assessment - AI Risk Monitoring and Reporting |
| 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 |
| AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Regulatory Compliance and Legal Considerations - AI Models, Frameworks, Strategies, and Use Cases - AI Organizational Processes and Alignment - AI Trustworthiness, Ethical and Societal Implications - AI Policies, Procedures, and Organizational Training |
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NEW QUESTION # 139
Which of the following testing approaches BEST helps to identify risk in an AI-powered customer support solution?
Answer: A
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. Adversarial testing deliberately supplies malformed, misleading, or hostile inputs to reveal failure modes that ordinary accuracy or load testing may miss. This is especially important for customer-facing AI where unexpected inputs can manipulate or degrade outputs. This makes option A, Using adversarial inputs to determine failure modes, 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
Which of the following is the MOST important consideration when selecting controls for AI systems?
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. Control selection should start with approved policy, governance, and oversight requirements.
Performance metrics, staff expertise, and integration with existing security processes are important implementation considerations, but controls must first be authorized and aligned with the organization ' s governance framework. This makes option A, Alignment with approved policy and oversight frameworks, 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 # 141
To reinforce organization-wide ethical norms and risk recognition, which of the following is MOST important to integrate into AI user training?
Answer: D
Explanation:
Effective AI user training must go beyond policy acknowledgment and compliance instruction to equip employees with the practical skills needed to identify ethical risks and report them appropriately. This builds an active risk-aware workforce.
Why B is Correct: The ISACA AAIR framework identifies that training on ethical risk indicators and reporting mechanisms directly reinforces ethical norms by enabling employees to recognize real-world signs of AI misuse, bias, or harmful outputs. When staff can identify specific risk signals and know how to escalate them, the organization builds a proactive risk culture grounded in practical ethical literacy.
Why A is Wrong: Acceptable use policy acknowledgment is a compliance activity, not a culture-building measure. Acknowledging a document does not ensure employees understand how to apply ethical principles in practice.
Why C is Wrong: Cyber threat identification addresses security risk, which is narrower than the full scope of ethical AI risk. Security training does not develop ethical judgment regarding fairness, bias, or societal impact.
Why D is Wrong: Regulatory compliance checklists address legal obligations but do not develop the ethical reasoning and risk recognition skills needed to reinforce organizational norms.
NEW QUESTION # 142
Which of the following is the PRIMARY benefit of defining and documenting a RACI matrix for AI solution development and deployment?
Answer: C
Explanation:
A RACI (Responsible, Accountable, Consulted, Informed) matrix is a governance tool that explicitly maps roles and decision authority across project activities. For AI systems, RACI frameworks ensure that accountability for decisions, outputs, and risk management is clearly defined and documented.
Why D is Correct: The ISACA AAIR curriculum identifies the RACI matrix as a foundational accountability instrument. Its primary benefit is establishing unambiguous responsibility and decision authority, which is essential for AI governance where multiple stakeholders-technical teams, business owners, risk practitioners, compliance officers-must work together with clear lanes of authority. This clarity prevents accountability gaps and ensures risk management actions are owned.
Why A is Wrong: Facilitating collaboration is a secondary benefit. While RACI does support cross-functional coordination, collaboration enablement is not its defining purpose. Collaboration can occur without a RACI through other mechanisms.
Why B is Wrong: Consolidating governance authority in senior leadership describes centralization, which is not the purpose of RACI. In fact, RACI typically distributes responsibility across multiple levels rather than consolidating it.
Why C is Wrong: Strengthening technical development governance is an application of the RACI, not its primary benefit. The RACI benefit is accountability clarity, which then supports technical and architectural governance.
NEW QUESTION # 143
Which of the following is the PRIMARY reason to include contractual requirements for model updates and disclosures from third-party AI suppliers?
Answer: B
Explanation:
Third-party AI suppliers introduce significant risk through model updates, changes in training data, and modifications to system behavior. Contractual disclosure requirements ensure the acquiring organization can maintain active risk oversight despite not controlling the vendor's development processes.
Why B is Correct: The ISACA AAIR framework emphasizes that third-party AI contracts must protect against harms arising from undisclosed changes. When vendors make silent updates to models, the acquiring organization cannot assess new risks before they affect users, decisions, or regulated outcomes. Timely disclosure requirements enable proactive risk detection and mitigation before individuals are harmed.
Why A is Wrong: Availability guarantees are service-level concerns addressed by SLA provisions. While important operationally, they do not address the risk management imperative of understanding what changes have been made to AI models.
Why C is Wrong: Internal trust-building is a change management consideration, not the primary purpose of contractual disclosure requirements. Contracts address risk obligations, not organizational confidence.
Why D is Wrong: Vendor staff access to sensitive datasets is a data access and privacy concern addressed through data processing agreements and access controls, not model update disclosure requirements.
NEW QUESTION # 144
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