This training offers a comprehensive program to master audits applied to Artificial Intelligence (AI). It enables participants to understand the specifics of AI audits, explore key compliance frameworks, and develop a practical methodology to effectively audit AI systems. |
Objectives | - Analyze the differences between traditional IT audits and audits specific to artificial intelligence
- Categorize and distinguish the types of AI audits (technical, ethical, compliance) according to their characteristics
- Use major frameworks (ISO/IEC 42001, NIST AI RMF, MITRE ATT&CK, TRiSM) to structure and conduct an AI audit
- Plan and carry out a complete AI audit following key steps: preparation, evidence collection, analysis, reporting
- Develop a customized checklist and implement internal practices to ensure continuity of AI audits
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Contents | Week 1
Audit Fundamentals - Definition and role of audits in IT and cybersecurity: discover the specifics, steps, and main challenges related to audits in artificial intelligence to ensure compliance and the security of digital systems.
Week 2
Typology and Use Cases of AI Audits - Discover the different types of AI audits: technical (model, data, security), ethical (bias, transparency, fairness), and governance and compliance. Explore practical cases: regulatory validation, bias reduction, and risk management.
Week 3
Frameworks & AI Audit Methodology - Overview of major AI frameworks: ISO/IEC 42001 for AI system management, NIST AI Risk Management Framework, MITRE ATT&CK for AI, TRiSM (Trust, Risk & Security Management), and responsible AI principles.
Week 4
Practical Application & Audit Simulation - Learn the AI audit methodology: planning, evidence collection, analysis, and reporting. Learn to map risks, define controls, create an AI checklist, and evaluate the compliance of an AI project through a case study.
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