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ISACA AAIA Exam Syllabus Topics:

SectionWeightObjectives
AI Governance and Risk33%- Privacy and Data Governance Programs
- AI Risk Management
- Ethics, Regulations, and Standards for AI
- AI Models, Considerations, and Requirements
- AI Governance and Program Management
AI Auditing Tools and Techniques21%- AI Audit Outputs and Reporting
- Data Quality and Analytics for AI Audit
- Audit Evidence Collection Techniques
- Audit Testing and Sampling Methodologies
- Audit Planning and Design
AI Operations46%- Performance Monitoring and Evaluation
- Incident Management and Resilience
- Operational Controls and Readiness
- AI System Lifecycle and Deployment
- Third-Party and Supply Chain Risk

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ISACA Advanced in AI Audit Sample Questions (Q278-Q283):

NEW QUESTION # 278
Which of the following is the GREATEST challenge when auditing an AI-based decision-making system?

Answer: D

Explanation:
The "Black Box" nature of many modern AI systems, particularly deep neural networks, makes it difficult to understand exactly how a decision was derived. "Understanding the transparency (and explainability) of AI models" is identified by the AAIATM manual as the greatest audit challenge because it limits the auditor's ability to verify fairness, detect hidden bias, or confirm compliance with logic-based regulations.


NEW QUESTION # 279
Which of the following is the GREATEST benefit of integrating AI in ransomware prevention?

Answer: A

Explanation:
Ransomware often involves subtle, unusual patterns of data access and encryption activity. The primary advantage of AI is its ability to "Analyze large volumes of data in real-time" to identify behavioral anomalies that traditional signature-based security tools might miss. AI can detect
"Zero-Day" ransomware by recognizing the intent of malicious actions (such as rapid file renaming or unauthorized encryption). This proactive detection is critical for stopping an attack before data exfiltration or total system lockout occurs.


NEW QUESTION # 280
An IS auditor is planning an audit covering a vendor-provided and supported AI model used by the organization to predict train track maintenance. Which of the following is the BEST approach for the IS auditor to test the model?

Answer: C

Explanation:
When auditing vendor-provided (third-party) AI models, the organization often lacks access to the underlying source code, neural network architecture, or weights. In such cases, the AAIATM manual recommends "Black Box Testing" as the most practical and effective approach. This involves testing the model based solely on its inputs and outputs to verify its predictive accuracy, fairness, and reliability without needing internal technical details.


NEW QUESTION # 281
An IS auditor is assessing whether an organization's AI risk taxonomy is complete. Which risk category is MOST often overlooked compared to traditional IT risk taxonomies?

Answer: A

Explanation:
Traditional IT risk taxonomies (CIA triad) do not natively capture AI-specific risks such as model bias, drift, and explainability failures, which require an extended taxonomy.


NEW QUESTION # 282
Which of the following is the MOST important risk for an IS auditor to consider when reviewing the adoption of an AI system?

Answer: D


NEW QUESTION # 283
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