AAIR: Advanced in AI Risk

By Isaca · Browse Mode
About the Exam

ISACA’s AAIR exam is a 90-question certification exam covering AI risk governance and framework integration, AI lifecycle risk management, and AI risk program management. It is intended for experienced IT risk professionals, including active CRISC holders and other qualified advanced-risk certification holders. Passing the exam is a required step toward earning the AAIR certification and demonstrates the ability to evaluate AI-related vulnerabilities, assess opportunities and impacts, and manage AI risk across the enterprise.

Exam Topics

  • AI Risk Governance and Framework Integration37%
  • AI Life Cycle Risk Management21%
  • AI Risk Program Management42%

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Last updated May 25, 2026 at 4:17 PM

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QuestionQ1

AI Life Cycle Risk Management

A risk practitioner is creating risk scenarios involving successful data-poisoning attacks against an AI model used throughout the organization. Which approach is BEST for helping ensure the scenarios are relevant?

Explanation

Engaging key stakeholders grounds AI data-poisoning scenarios in the organization’s actual business processes, model uses, data dependencies, and impact concerns, making the scenarios relevant to organizational risk.

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QuestionQ2

AI Risk Governance and Framework Integration

Which of the following is a risk practitioner’s BEST recommendation for establishing accountability for AI system outputs and decisions?

Explanation

Documented role assignments with named owners establish clear responsibility and accountability for AI system outputs and decisions.

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QuestionQ3

AI Life Cycle Risk Management

What is the PRIMARY purpose of maintaining comprehensive model cards and documentation?

Explanation

Comprehensive model cards and documentation provide transparency about a model’s purpose, capabilities, limitations, performance, and risks, enabling informed and responsible use.

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QuestionQ4

AI Risk Governance and Framework Integration

Which of the following BEST enables an organization that is adopting AI solutions to foster an ethical, risk-aware culture?

Explanation

Leadership that consistently models ethical behavior and values in AI development and use establishes the norms that shape organizational culture, decision-making, and accountability for AI risks.

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QuestionQ5

AI Life Cycle Risk Management

To strengthen organization-wide ethical norms and awareness of risk, which of the following is MOST important to incorporate into AI user training?

Explanation

Ethical-risk indicators and reporting procedures enable AI users to recognize potential ethical harms, identify concerns early, and escalate them through appropriate channels. This directly supports a shared culture of responsible AI use and proactive risk management.

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