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ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Risk Governance and Framework Integration | 37% | - AI Organizational Processes and Alignment - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases |
| Topic 2: AI Life Cycle Risk Management | - AI model and data risk identification - AI bias, drift, transparency, and control evaluation - AI development, deployment, and monitoring risks | |
| Topic 3: AI Risk Program Management | 42% | - AI governance communication and reporting - AI risk monitoring and continuous improvement - Enterprise AI risk program design - AI risk assessment and treatment strategies |
ISACA Advanced in AI Risk Sample Questions:
Question 1
Which of the following is the MOST important benefit of deploying continuous monitoring and automated anomaly detection for AI models in production?
A. Improved alignment of model outputs and behavior with organizational strategic goals
B. Enhanced interpretability and transparency of model decisions
C. Timely identification of adversarial intrusions and unauthorized parameter changes
D. Automated risk register and vulnerability database updates
Question 2
Which of the following is the MOST important consideration when managing changes to an AI model in production?
A. Conducting rigorous validation to assess effects on predictive accuracy and model bias
B. Expediting rollout of changes in production to ensure service continuity and minimize downtime
C. Implementing stringent approval processes for user access to new model functionalities
D. Allowing operational teams to adjust configuration parameters for real-time performance tuning
Question 3
A risk practitioner is reviewing an organization's implementation of a business-critical AI decision system.
Which of the following would be of GREATEST concern?
A. Insufficient scenario-based testing of system failure modes and recovery procedures
B. Reliance on conventional third-party security providers for system monitoring
C. Lack of cross-functional AI incident identification and escalation training
D. Risk threshold acceptance criteria that do not require 100% decision accuracy
Question 4
Which of the following BEST helps to ensure adherence to data minimization principles when using an AI model whose training dataset contains personal information?
A. Data encryption
B. Data loss prevention (DLP)
C. Pseudonymization
D. Role-based access control (RBAC)
Question 5
Which of the following is a risk practitioner's BEST justification for embedding AI risk considerations into acceptable use policies?
A. Maintaining alignment of enterprise tolerance across decision-making systems
B. Applying uniform risk controls across diverse business functions
C. Addressing the potential for shadow AI by defining an allow list for AI tools
D. Assigning AI risk accountability to business unit leadership
Solutions:
| Question 1 Answer: C | Question 2 Answer: A | Question 3 Answer: A | Question 4 Answer: C | Question 5 Answer: A |
