عراب ال IT 
امتحانات دوليه
(AAIA)
Advanced in AI Audit
About the Certification
This is an advanced professional certification specialized in Artificial Intelligence (AI) Auditing, offered by ISACA. It focuses on evaluating, governing, and managing risks related to the use of AI within organizations. The certification aims to prepare professionals to understand how AI systems are designed and operated, and to assess them from governance, risk, compliance, and ethics perspectives, ensuring transparency, fairness, and regulatory compliance. It covers areas such as AI models, data quality, risk management, control frameworks, and compliance with relevant standards and regulations. This makes the certification well suited for auditors, governance and risk professionals, technologists, and decision-makers, and represents an advanced credential for enterprise environments adopting AI in a responsible and well-governed manner.
Main Curriculum
The curriculum is divided into three main sections
- AI Governance and Risk Management
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- AI governance principles
- Regulatory frameworks and organizational policies
- AI risk management
- Roles, responsibilities, and oversight
- AI Systems Lifecycle and Controls
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- AI system lifecycle
- AI model design and development
- Technical and operational controls
- Data and model quality
- AI Auditing and Compliance
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- Auditing AI system operations
- Transparency and explainability
- Ethical and regulatory compliance
- Audit reporting and recommendations
Exam Details
- Exam code: AAIA
- Duration: 210 minutes
- Number of questions: 120
- Question types: Multiple-choice
- Language: English
- Passing score: 450 out of 800
- Exam fee: USD 575–760 (varies by country and may include taxes)
- Certification Maintenance The certification does not expire automatically Requires 20 CPE credits per year, totaling 120 CPE credits over 3 years Annual maintenance fee applies
Do I need certifications before it ?
No, not at all.
However, it is recommended to have a solid understanding of AI technologies, AI governance, and audit and risk management concepts related to intelligent systems, which helps significantly in mastering the certification content.
Which certifications are recommended after this one ?
Not mandatory.
However, for professionals seeking a strong path in AI Auditing especially in AI governance, risk management, compliance validation, and ethics the AAIA (Advanced in AI Audit) certification is the strongest specialization.
What are the main career uses of the AAIA certification ?
- AI Governance & Responsible AI to establish governance frameworks ensuring transparency, fairness, and accountability.
- AI Risk Management & Model Assurance to identify and assess AI model risks and validate output reliability.
- Algorithm Auditing & Explainable AI (XAI) to audit algorithms, understand decision-making processes, and reduce bias.
- Data Quality, Bias, and Ethics Audits to evaluate data integrity, bias sources, and ethical compliance.
- Regulatory Compliance for AI Systems to align AI solutions with emerging global regulations.
- Roles such as AI Auditor, AI Risk & Governance Specialist, or Technology Assurance Lead.
Your Step Toward Professional AI Systems Auditing :
This certification empowers you to assess and audit information systems, technical architectures, and security controls using a structured, enterprise-grade approach. It enables early identification of operational and security gaps, alignment of risks with governance and compliance, and delivery of clear, actionable audit recommendations with reduced noise and higher accuracy. It is a strong foundational step for professionals seeking specialization in IT Auditing and AI Assurance, backed by an internationally recognized ISACA credential.
Who is this certification suitable for ?
- Professionals working in IT, Cloud, Security, Infrastructure, Audit, Risk, or Governance.
- Individuals auditing or assessing AI systems from a professional and regulatory perspective.
- Specialists involved in AI Governance and AI Risk Management.
- Professionals interested in bias, transparency, and ethical risks in AI systems.
- Those planning to specialize in AI Audit and Responsible AI.