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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Risk Governance and Framework Integration | 37% | - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases - AI Ownership, Oversight, and Accountability |
| Topic 2: AI Risk Program Management | 42% | - Enterprise AI risk program design - AI governance communication and reporting - AI risk assessment and treatment strategies - AI risk monitoring and continuous improvement |
| Topic 3: AI Life Cycle Risk Management | - AI model and data risk identification - AI development, deployment, and monitoring risks - AI bias, drift, transparency, and control evaluation |
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NEW QUESTION # 78
Which of the following is MOST important to verify when assessing open-source AI components in 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. Open-source AI components should be traceable so the organization can verify origin, dependencies, integrity, licensing, and maintenance history. Geography and cost are secondary, and documentation ownership alone does not establish trustworthy provenance. This makes option A, Traceability for open-source AI artifacts, 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
An organization depends on automated decision systems for critical operations. Which of the following MOST effectively mitigates prolonged operational risk after system failures?
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. Tabletop disaster recovery exercises test whether recovery roles, procedures, escalation paths, dependencies, and decisions will work during disruption. Restoration of artifacts is necessary after failure, but exercises validate the organization ' s ability to recover before an incident occurs. This makes option C, Conducting tabletop disaster recovery exercises, 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
Which of the following is the PRIMARY benefit of retraining an AI model with refreshed data?
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. Retraining with refreshed data allows a model to learn current patterns and reduce errors caused by outdated examples or changing real-world relationships. Hyperparameter tuning and stakeholder feedback are separate activities, while privacy deletion is a governance requirement rather than the main performance benefit. This makes option C, Reducing errors and misclassifications by allowing the model to learn from recent examples, 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 # 81
An organization has deployed an AI system to automate critical data analysis functions. Which of the following is the MOST appropriate way for the risk practitioner to assess the multiple sources of risk associated with this situation?
Answer: A
Explanation:
When multiple risk sources are present in a critical AI deployment, the risk practitioner must apply a prioritization framework that focuses resources on the risks with the greatest potential for organizational harm. This risk-based prioritization is more effective than comprehensive but undifferentiated risk cataloging.
Why A is Correct: The ISACA AAIR risk assessment methodology prioritizes risk factors based on potential harm severity as the most appropriate approach for critical AI systems. Focusing on risks most likely to generate substantial harm ensures that the organization's risk management resources are directed toward the exposures that matter most-protecting the critical functions that the AI system supports and preventing the most consequential adverse outcomes.
Why B is Wrong: Quantifying competitors' risk events provides external benchmarking data but cannot accurately characterize the organization's specific risk profile. Competitor risk events may involve different AI architectures, use cases, and organizational contexts that make direct comparison unreliable.
Why C is Wrong: Rating each risk factor independently without integration produces a fragmented view that misses risk correlations, cascade effects, and the compounding nature of multiple simultaneous risk factors.
Independent ratings also do not inherently lead to the harm-based prioritization needed for critical systems.
Why D is Wrong: Documenting technical limitations is a useful input to risk identification but represents a technical inventory activity rather than a comprehensive risk assessment methodology. Technical limitations are one category of risk factor among many-operational, governance, data quality, and third-party risks also require assessment.
NEW QUESTION # 82
The PRIMARY reason to transfer residual AI risk to a third party is to:
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. Risk transfer is used when a third party assumes defined financial or contractual consequences of residual risk that the organization cannot or chooses not to retain. It can reduce organizational liability, but it does not eliminate the organization ' s governance responsibilities. This makes option A, lower organizational liability when internal mitigations fail, 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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