AAIA - Complete Course | Audit AI Governance and Controls

This course contains the use of artificial intelligence.

Cyvitrix Learning creates and reviews the curriculum, scripts, explanations, and examples. Human subject matter experts remain responsible for accuracy, quality, and updates.

AI assurance requires more than recognizing terminology. Auditors must connect governance, model operations, technical risk, control design, evidence, and reporting. This full instructional course develops that connected view for professionals preparing for ISACA Advanced in AI Audit topics or expanding from traditional IT audit into AI assurance.

The curriculum begins with AI governance and risk management, then compares global frameworks and examines ISO/IEC 42001. You will explore AI ethics, bias, responsible data use, AI security threats, lifecycle oversight, and operational controls. Dedicated modules cover AI audit methods and evidence, emerging assurance and compliance topics, and the way AI integrates with enterprise functions.

Throughout the course, you will practice defining audit scope, identifying risks and control objectives, selecting procedures, evaluating evidence, and communicating findings. Practical scenarios connect governance decisions with data quality, model development, monitoring, change management, fairness, explainability, security, and incident response. The course includes structured explanations, quizzes, and review resources. It is a full teaching course, not a practice-exam-only product, and it does not promise an exam result.

This course is intended for internal and external auditors, GRC and risk professionals, information security teams, data-governance specialists, AI program leaders, and AAIA candidates. Prior experience in audit, risk, security, data, or AI will help, but the course introduces the governance and lifecycle context needed to follow the material.

Production and independence disclosure: the course uses AI-assisted content production and narration. Educational material is authored, structured, scripted, and reviewed by subject matter experts. This is independently developed training, not official ISACA training, and it is not sponsored, endorsed, or approved by ISACA. Certification names and trademarks belong to their respective owners and are used for identification only.

What you will be able to do

• Assess AI governance structures, accountability, risk, privacy, and responsible-use controls.

• Evaluate data quality, model lifecycle, monitoring, change, and operational controls for AI systems.

• Plan an AI audit by defining scope, risks, criteria, procedures, sampling, and evidence needs.

• Test controls and document evidence for fairness, explainability, access, security, and model performance.

• Analyze AI threats and vulnerabilities and select relevant audit responses.

• Map ISO/IEC 42001 and NIST AI RMF concepts to AI assurance work.

How to get the most from this course

1. Follow the sections in order so the concepts build into a connected professional workflow.

2. Pause after each major topic and relate the decision, evidence, or control to your own environment.

3. Use the scenarios and review activities to test your reasoning, not only your recall.

4. Use the course Q&A when a concept, decision, or example needs clarification.