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Updated: Oct 03, 2026
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ISACA AAIR Exam Overview:
| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | ISACA Advanced in AI Risk (AAIR) Certification Exam |
| Exam Number: | AAIR |
| Real Exam Qty: | 90 |
| Exam Price: | USD 459 (member) / USD 599 (non-member) |
| Exam Format: | Proctored exam (test center or remote where available), Computer-based testing, Multiple-choice |
| Available Languages: | English, Spanish, Chinese (Simplified) |
| Exam Duration: | 150 minutes |
| Related Certifications: | CISA CRMA CGEIT CRISC CISSP CDPSE CGRC CISM |
| Recommended Training: | AAIR QAE Practice Database (ISACA Learning Resources) AAIR Online Review Course (ISACA) AAIR Virtual Workshop (ISACA Training) |
| Exam Registration: | ISACA Certification Registration (MyISACA portal) ISACA AAIR Official Certification Page |
| Sample Questions: | ISACA AAIR Sample Questions |
| Exam Way: | Computer-based exam via PSI testing centers or remote proctoring (availability varies by region; some regions require test center only). |
| Pre Condition: | Candidates must hold one of ISACA or equivalent recognized certifications such as CISA, CISM, CRISC, CGEIT, CDPSE, CISSP, CRMA, CGRC, or other approved risk/security/audit designations, and have relevant IT risk or advisory experience. |
| Official Syllabus URL: | https://www.isaca.org/credentialing/aair |
ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| AI Risk Program Management | 42% | - AI governance communication and reporting - AI risk assessment and treatment strategies - AI risk monitoring and continuous improvement - Enterprise AI risk program design |
| AI Risk Governance and Framework Integration | 37% | - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases - AI Ownership, Oversight, and Accountability |
| AI Life Cycle Risk Management | - AI model and data risk identification - AI development, deployment, and monitoring risks - AI bias, drift, transparency, and control evaluation |
ISACA Advanced in AI Risk Sample Questions:
Which of the following is the PRIMARY risk reduction benefit of embedding secure coding practices throughout the AI development life cycle?
- A. Fewer model vulnerabilities that can be exploited by malicious actors
- B. Increased predictive accuracy in production environments
- C. Reduced need for manual review of model outputs and decisions
- D. More rapid detection of model drift during pre-deployment testing
Correct Answer: A 🗳️
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The MOST important consideration when reviewing existing business processes to determine their suitability for AI integration is whether:
- A. the AI tools can be implemented immediately at scale.
- B. the AI tools have been adopted widely within the industry.
- C. the process includes clearly defined rules for AI tools to follow.
- D. staffing requirements and costs can be reduced by using AI tools.
Correct Answer: C 🗳️
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Which of the following is the PRIMARY reason to lower AI model temperature?
- A. To enhance consistency and accuracy of model outputs
- B. To diversify ideas and recommendations generated by the model
- C. To reduce energy consumption and environmental impact
- D. To mitigate the risk of persistent bias in responses to users
Correct Answer: A 🗳️
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A risk practitioner discovers that autonomous agents have been creating temporary HR system identities.
Which of the following poses the GREATEST risk?
- A. Increased staffing needs for human validation
- B. Identities are not incorporated into the federated system
- C. Delays in breach identification and response
- D. Ineffective credential management
Correct Answer: B 🗳️
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An organization deploys an AI credit scoring model trained on historical financial data that underrepresents certain demographic groups. Which of the following is the risk practitioner ' s BEST recommendation to mitigate this risk?
- A. Define specific inclusivity goals and expand data to a broader range of sources.
- B. Implement reporting for model drift and anomalous model decisions.
- C. Notify stakeholders that the model may not always reflect standard loan approval thresholds.
- D. Use unsupervised learning to identify hidden or complex discriminatory patterns in the dataset.
Correct Answer: A 🗳️
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