Pass Guaranteed 2026 ISACA AAIR: ISACA Advanced in AI Risk Authoritative Valid Exam Review

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ISACA AAIR Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Risk Program Management42%- AI Risk Monitoring and Reporting
- AI Risk Assurance and Continuous Improvement
- AI Risk Response and Mitigation
- AI Risk Identification and Assessment
Topic 2: AI Risk Governance and Framework Integration37%- AI Models, Frameworks, Strategies, and Use Cases
- AI Organizational Processes and Alignment
- AI Trustworthiness, Ethical and Societal Implications
- AI Regulatory Compliance and Legal Considerations
- AI Policies, Procedures, and Organizational Training
- AI Ownership, Oversight, and Accountability
Topic 3: AI Life Cycle Risk Management21%- AI Data and Asset Management
- AI Implementation, Maintenance, and Decommissioning
- AI Model Training, Testing, and Validation
- AI Design, Development/Procurement, and Documentation

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ISACA Advanced in AI Risk Sample Questions (Q90-Q95):

NEW QUESTION # 90
Which of the following BEST helps to ensure AI model outputs can be reproduced in other environments?

Answer: D

Explanation:
AI model reproducibility-the ability to recreate identical or near-identical outputs in different environments-depends on having access to the exact training data, model weights, and configurations used to produce a given model version. Training dataset snapshots are foundational to this capability.
Why B is Correct: The ISACA AAIR model documentation and auditability guidance identifies capturing and archiving complete training dataset snapshots as essential for reproducibility. To reproduce a model's outputs in another environment, the development team must be able to reconstruct the exact training conditions- including the precise dataset used. Without archived snapshots, datasets evolve and the original training conditions become impossible to recreate.
Why A is Wrong: Manual review of outputs validates accuracy for a specific deployment but does not address reproducibility across environments. Manual review cannot substitute for the technical artifacts needed to recreate a model.
Why C is Wrong: Continuous performance monitoring detects behavioral changes in production but does not enable reproduction of the model in alternative environments. Monitoring is forward-looking, while reproducibility is about reconstructing past conditions.
Why D is Wrong: AI-specific change management processes control how models are modified and deployed but do not capture the training artifacts needed for environmental reproduction. Change management governs transitions; reproducibility requires data preservation.


NEW QUESTION # 91
A healthcare organization plans to use synthetic records in medical research to help protect patient privacy.
Which of the following is the GREATEST risk associated with using synthetic data to train AI models?

Answer: B

Explanation:
Synthetic data is generated algorithmically to resemble real data while protecting individual privacy.
However, synthetic data generation processes may not perfectly capture the full statistical diversity of real- world populations-particularly rare conditions, edge cases, and underrepresented demographic groups.
Why A is Correct: According to ISACA AAIR data quality guidance for AI, the greatest risk of training on synthetic data is that it may not reflect real-world diversity. In healthcare, this is particularly consequential because AI models trained on non-diverse synthetic data may perform poorly for patient populations not well- represented in the original real data-potentially producing inaccurate diagnoses or treatment recommendations for vulnerable groups, perpetuating health inequities.
Why B is Wrong: While reduced diversity could contribute to increased false negatives in some scenarios, this is a specific manifestation of the broader diversity problem. The root cause-lack of real-world representativeness-is the more fundamental and comprehensive risk.
Why C is Wrong: Regulatory noncompliance from synthetic data use depends on jurisdiction-specific requirements. Many regulations explicitly encourage synthetic data to protect privacy. While compliance must be verified, it is not the greatest inherent risk of synthetic data quality.
Why D is Wrong: Synthetic data generation occurs in controlled internal environments and is not inherently more susceptible to data poisoning than other data types. Poisoning risk is a function of data pipeline controls, not whether data is synthetic or real.


NEW QUESTION # 92
An organization deploys an autonomous system that makes decisions affecting compliance with regulations.
If those decisions could potentially produce regulatory breaches, which of the following BEST helps to manage associated liability exposures?

Answer: A


NEW QUESTION # 93
An organization depends on automated decision systems for critical operations. Which of the following MOST effectively mitigates prolonged operational risk after system failures?

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. 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 # 94
Which of the following is the GREATEST risk when an AI system requires a specific safeguard that cannot be put in place because of technical constraints?

Answer: D

Explanation:
When required safeguards cannot be technically implemented, the risk they were designed to mitigate remains unaddressed. This creates a residual exposure gap where the AI system operates with known, unmitigated vulnerabilities-a fundamental risk management failure for the identified threat.
Why A is Correct: The ISACA AAIR risk treatment guidance identifies elevated residual exposure from absent controls as the greatest risk when required safeguards cannot be implemented. Every required safeguard addresses a specific risk exposure. When that safeguard is technically infeasible, the risk it was designed to prevent remains fully present. This unmitigated exposure may exceed the organization's risk tolerance and require escalation to senior management for risk acceptance or alternative treatment decisions.
Why B is Wrong: Training dataset restrictions relate to model development constraints, not directly to the inability to implement a specific runtime safeguard. This is a separate concern that may arise in some technical constraint scenarios but is not the primary risk of an absent safeguard.
Why C is Wrong: User experience degradation is an operational quality concern. Performance impacts from technical constraints are a usability issue rather than a risk exposure representing the greatest organizational concern.
Why D is Wrong: Operational inefficiency and manual process dependencies are resource and process concerns. While relevant to operational cost and effectiveness, they do not represent the primary risk of an unmitigated security or safety exposure from an absent safeguard.


NEW QUESTION # 95
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