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ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Life Cycle Risk Management | 21% | - AI Implementation, Maintenance, and Decommissioning - AI Data and Asset Management - AI Design, Development/Procurement, and Documentation - AI Model Training, Testing, and Validation |
| Topic 2: AI Risk Program Management | 42% | - AI Risk Response and Mitigation - AI Risk Identification and Assessment - AI Risk Monitoring and Reporting - AI Risk Assurance and Continuous Improvement |
| Topic 3: AI Risk Governance and Framework Integration | 37% | - AI Regulatory Compliance and Legal Considerations - AI Organizational Processes and Alignment - AI Trustworthiness, Ethical and Societal Implications - AI Ownership, Oversight, and Accountability - AI Policies, Procedures, and Organizational Training - AI Models, Frameworks, Strategies, and Use Cases |
ISACA Advanced in AI Risk Sample Questions:
1. Which of the following is the PRIMARY benefit of implementing a comprehensive data pipeline for AI model training, testing, and validation?
A) Automation of complex tasks in early stages of the data pipeline
B) Sharing of governance risk with external data and service providers
C) Enhanced auditability of outputs to provide evidence of regulatory compliance
D) Reduced risk of introducing errors into the final AI model
2. After which of the following events is it MOST important to update risk ratings?
A) Creation of a new AI risk oversight committee
B) Discovery of discriminatory outputs from an AI system
C) Addition of new metrics tracked by automated monitoring
D) Vulnerability patch deployment for an AI system
3. A manufacturing organization has implemented an autonomous navigation system for warehouse operations.
Which of the following should a risk practitioner regard as the MOST significant concern?
A) The system is used to accelerate just-in-time warehouse processes.
B) The system is unable to learn from complex situations not encountered during training.
C) The organization uses outside contractors to address the lack of in-house AI knowledge.
D) The deep neural network used by the system contains datasets with proprietary information.
4. Which of the following poses the GREATEST challenge when performing root cause analysis for incidents involving AI systems and data?
A) Privacy compliance
B) Automation bias
C) Lack of transparency
D) Unclear system objectives
5. Which of the following is the PRIMARY benefit of integrating AI-driven business intelligence into enterprise risk processes?
A) Enhanced alignment of analysis outputs with organizational risk thresholds
B) Automated production of technical performance reports for AI business tools
C) Reduced costs through elimination of redundant business risk oversight mechanisms
D) Centralized governance of AI inventory and classification activities
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: A |





