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ISACA AAIR - ISACA Advanced in AI Risk

Updated: Jul 30, 2026

Q & A: 92 Questions and Answers

AAIR Braindumps VCE
  • Exam Code: AAIR
  • Exam Name: ISACA Advanced in AI Risk

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ISACA AAIR Exam Syllabus Topics:

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

ISACA Advanced in AI Risk Sample Questions:

1. 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


2. An organization uses an AI model that learns from live data streams. Which of the following is the BEST course of action to manage the risk of an adaptive model?

A) Utilize a defense-in-depth control approach for model access.
B) Apply dynamic performance thresholds and conduct scheduled recalibrations.
C) Implement automated monitoring to detect data drift and data poisoning.
D) Restrict data sources and perform periodic data quality inspections.


3. Which of the following is the MOST important consideration when managing changes to an AI model in production?

A) Expediting rollout of changes in production to ensure service continuity and minimize downtime
B) Allowing operational teams to adjust configuration parameters for real-time performance tuning
C) Conducting rigorous validation to assess effects on predictive accuracy and model bias
D) Implementing stringent approval processes for user access to new model functionalities


4. To reinforce organization-wide ethical norms and risk recognition, which of the following is MOST important to integrate into AI user training?

A) Acceptable use policy and acknowledgment
B) External regulations and compliance checklists
C) Cyber threat identification and AI incident handling
D) Ethical risk indicators and reporting


5. An election oversight body is considering the use of AI to identify irregularities in voting patterns. Which of the following is the MOST important risk to evaluate?

A) Susceptibility to contextual drift
B) Identification of voter locations
C) Amplification of biases in historical data
D) Distrust of AI among political interest groups


Solutions:

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

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