ISACA Advanced in AI Risk: AAIR Exam

"ISACA Advanced in AI Risk", also known as AAIR exam, is a ISACA Certification. With the complete collection of questions and answers, PrepPDF has assembled to take you through 92 Q&As to your AAIR Exam preparation. In the AAIR exam resources, you will cover every field and category in AI Risk Certification helping to ready you for your successful ISACA Certification.

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  • Exam Code: AAIR
  • Exam Name: ISACA Advanced in AI Risk
  • Certification Provider: ISACA
  • Corresponding Certification: AI Risk
  • Updated: Aug 14, 2026
  • No. of Questions: 92 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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ISACA AAIR Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Life Cycle Risk Management- AI development, deployment, and monitoring risks
- AI bias, drift, transparency, and control evaluation
- AI model and data risk identification
Topic 2: AI Risk Program Management42%- AI governance communication and reporting
- Enterprise AI risk program design
- AI risk assessment and treatment strategies
- AI risk monitoring and continuous improvement
Topic 3: AI Risk Governance and Framework Integration37%- AI Ownership, Oversight, and Accountability
- AI Organizational Processes and Alignment
- AI Models, Frameworks, Strategies, and Use Cases

ISACA Advanced in AI Risk Sample Questions:

1. Which of the following is the PRIMARY benefit of tailoring AI governance to an organization's culture and risk tolerance?

A) Improved AI model explainability and regulatory compliance
B) Enhanced AI training programs and staff reskilling initiatives
C) Higher stakeholder acceptance rates and more appropriate AI risk policies
D) Automation of risk assessment processes and clearer AI risk accountability


2. A risk practitioner learns that an organization's AI inventory includes separate listings of AI systems, models, and datasets. Which of the following is the risk practitioner's BEST recommendation to improve AI governance?

A) Map interdependencies between AI assets continuously.
B) Assign inventory oversight to the AI risk committee.
C) Automate inventory reconciliation steps.
D) Include information about model training frequency.


3. Which of the following BEST mitigates risk associated with evasion attacks on AI models?

A) Predictive analytics
B) Anomaly detection
C) API rate limiting
D) Feature importance weighting


4. Which of the following is the GREATEST benefit of incorporating AI technology for data asset management?

A) Reducing the initial impacts of data poisoning and exfiltration attacks
B) Automating data cleaning and metadata tagging for large datasets
C) Justifying the use of synthetic data to augment smaller datasets
D) Providing more rapid identification of overfitting during model training


5. Which of the following is a risk practitioner's BEST recommendation to establish accountability for AI system outputs and decisions?

A) Formal documented role assignments with named owners
B) Regular reviews of resource allocation for AI projects
C) Continuous monitoring and key performance indicators (KPIs)
D) Centralized governance task force for model decision authority


Solutions:

Question # 1
Answer: C
Question # 2
Answer: A
Question # 3
Answer: B
Question # 4
Answer: B
Question # 5
Answer: A

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