ISACA AAIR Exam Overview:
| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Risk™ Exam |
| Exam Number: | AAIR |
| Exam Duration: | 150 minutes |
| Passing Score: | 450 (scaled score, max 800) |
| Exam Price: | US$459 (Member), US$599 (Non-Member) |
| Certificate Validity Period: | 3 years |
| Available Languages: | Spanish, English |
| Real Exam Qty: | 90 |
| Related Certifications: | CGEIT CGRC CRMA CRISC CDPSE CRMP CISM CISA |
| Exam Format: | Multiple-choice, Scenario-based |
| Recommended Training: | AAIR Virtual Workshop AAIR Online Review Course AAIR Review Manual |
| Exam Registration: | Official Registration |
| Sample Questions: | ISACA AAIR Sample Questions |
| Exam Way: | Computer-based; authorized PSI testing centers or remote proctored (remote not available in India, Mainland China, Hong Kong) |
| Pre Condition: | Hold active, good-standing certification: CISA, CISM, CRISC, CGEIT, CDPSE, CRMP, CRMA, CGRC, CISSP, CERP, CRCM, PMI-RMP or other approved credentials |
| Official Syllabus URL: | https://www.isaca.org/credentialing/aair/aair-exam-content-outline |
ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| AI Risk Program Management | 42% | - AI Risk Identification and Assessment - AI Risk Response and Mitigation - AI Risk Monitoring and Reporting - AI Risk Assurance and Continuous Improvement |
| 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 Policies, Procedures, and Organizational Training - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases |
| AI Life Cycle Risk Management | 21% | - AI Data and Asset Management - AI Design, Development/Procurement, and Documentation - AI Model Training, Testing, and Validation - AI Implementation, Maintenance, and Decommissioning |
ISACA Advanced in AI Risk Sample Questions:
Question 1
A risk practitioner assesses a new AI system and determines that the risk is within the organization's risk tolerance. Which of the following is the BEST recommendation to ensure system controls remain effective over time?
A. Alignment with recognized AI control frameworks
B. Periodic regulatory compliance reviews
C. Ongoing AI security and risk awareness training
D. Continuous monitoring for data and performance drift
Question 2
Which AI security by design option BEST mitigates targeted model poisoning and supply chain tampering?
A. Use data tokenization for sensitive fields
B. Frequent data refreshes with checksums
C. Frequent model retraining and bias monitoring
D. Adversarial resilience and data integrity controls
Question 3
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
Question 4
Which of the following would be of GREATEST concern to a risk practitioner reviewing the testing and validation of an AI-driven technical support system?
A. Inaccurate outputs resulting from model drift
B. Infrequent incorporation of updated training datasets
C. Insufficient encryption of data at rest and in transit
D. Excessive dependence on manual sampling
Question 5
Which of the following is a risk practitioner's BEST recommendation to establish accountability for AI system outputs and decisions?
A. Regular reviews of resource allocation for AI projects
B. Formal documented role assignments with named owners
C. Centralized governance task force for model decision authority
D. Continuous monitoring and key performance indicators (KPIs)
Solutions:
| Question 1 Answer: D | Question 2 Answer: D | Question 3 Answer: A | Question 4 Answer: A | Question 5 Answer: B |

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