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| Section | Objectives |
|---|---|
| AI Risk Management | - Risk identification and assessment for AI systems
|
| AI Lifecycle Controls | - Controls across AI development lifecycle
|
| Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
| AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
| Regulatory and Compliance Requirements | - Global AI regulatory landscape
|
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NEW QUESTION # 78
Which of the following is the risk practitioner ' s FIRST course of action upon learning that an AI model has been providing responses that are outside predefined thresholds for accuracy?
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. A breach of a predefined accuracy threshold is a governance event, so the first action is to notify the designated AI governance owner with decision authority. Technical investigation and risk-register updates can follow once the accountable owner has been informed. This makes option C, Notify designated AI governance owners for decision making, 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
Which of the following is the GREATEST concern when an organization cannot clearly explain an AI system
' s decision-making process and the origin of its inputs?
Answer: C
Explanation:
Explainability and input transparency are foundational requirements for responsible AI governance. When these are absent, organizations lose the ability to identify when AI systems produce harmful, biased, or inaccurate results-leaving those harms undetected and unaddressed.
Why C is Correct: According to ISACA AAIR, the inability to explain AI decisions is most dangerous because it creates an environment where discriminatory or inaccurate outputs can persist undetected. This exposes the organization to regulatory penalties (particularly under anti-discrimination, financial services, and privacy laws), reputational damage, and harm to affected individuals. The detection gap-not knowing what the system is doing wrong-is the core governance failure.
Why A is Wrong: External provider dependence is a third-party risk management concern. While relevant, it is a structural risk that can be addressed through contract management, not an immediate consequence of lacking explainability.
Why B is Wrong: Declining adoption rates represent a change management and trust concern. Business unit reluctance to adopt AI is a cultural and operational issue, not the primary risk from unexplainable AI decisions.
Why D is Wrong: Manual review bottlenecks represent operational inefficiency. They may result from lack of confidence in AI outputs but do not represent the primary organizational harm from unexplainability.
NEW QUESTION # 80
Which of the following is a risk practitioner's BEST recommendation to establish accountability for AI system outputs and decisions?
Answer: A
Explanation:
Accountability in AI governance requires that specific individuals or roles be clearly designated as responsible for AI system outputs, decisions, and associated risks. Without formal documentation of ownership, accountability gaps emerge.
Why D is Correct: The ISACA AAIR framework emphasizes that accountability must be explicit and documented, with named individuals assigned to own AI outcomes. Formal role assignments create a traceable chain of responsibility that supports auditability, regulatory compliance, and effective escalation when issues arise. Named ownership prevents diffusion of responsibility.
Why A is Wrong: A centralized task force creates collective responsibility, which can dilute individual accountability. Governance bodies support oversight but do not replace individual role ownership for specific outputs.
Why B is Wrong: Continuous monitoring and KPIs are valuable operational controls but represent monitoring mechanisms, not accountability structures. Monitoring detects issues but does not assign responsibility for them.
Why C is Wrong: Resource allocation reviews address investment efficiency rather than accountability for AI decisions and outputs. This is a management activity, not an accountability framework.
NEW QUESTION # 81
An organization integrates multiple AI services using APIs to enhance a customer support chatbot. Which of the following is the GREATEST risk?
Answer: C
Explanation:
API integration with external AI services creates data transmission pathways between the organization and external systems. Customer support contexts involve sensitive personal data-account information, contact details, inquiry content-that may be transmitted through these API connections.
Why B is Correct: The ISACA AAIR security and privacy guidance identifies unauthorized disclosure of sensitive data through insecure API connections as the greatest risk in multi-service AI integration. APIs can be vulnerable to interception, inadequate authentication, or misconfiguration. In a customer support context, exposure of personal data via API vulnerabilities creates privacy violations, regulatory liability, and reputational harm-all more severe than the other listed concerns.
Why A is Wrong: Bias and inaccuracy in chatbot responses are real quality risks but represent service quality issues rather than security or privacy breaches. Inaccurate responses are visible and correctable; data breaches may go undetected.
Why C is Wrong: Customer dissatisfaction from operational delays is a service quality and business risk. It is a manageable consequence of performance issues rather than the greatest risk from API-based AI integration.
Why D is Wrong: Insufficient training datasets affect model quality but are a development concern addressed during the model selection phase. They do not represent the primary operational risk of deploying multi- service API integrations in production.
NEW QUESTION # 82
Which of the following BEST helps to ensure the success of an AI risk management plan?
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 successful AI risk management plan depends on robust governance and ethical oversight that establishes accountability, escalation, decision rights, and coordinated monitoring. Individual security or IP controls address only portions of the overall program. This makes option B, Robust structures for governance and ethical oversight, 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 # 83
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