Course description

This practitioner course turns ISO/IEC 42001 into a practical blueprint for establishing, implementing, maintaining, and improving an Artificial Intelligence Management System (AIMS). We link strategy and policy to clear governance, roles, and accountability for AI products and services. You’ll learn to scope your AIMS, identify stakeholders, and run risk/impact assessments that address safety, bias/fairness, privacy, security, and explainability. We translate lifecycle controls into day-to-day practices: data management, model design and testing, validation, deployment, monitoring, incident/change management, and decommissioning. The course covers documentation and traceability, transparency measures, human oversight, supplier/third-party model management, and metrics for performance and harm reduction. You’ll prepare audit-ready evidence, internal audit plans, and management review inputs that drive continual improvement and align with broader IMS or ESG commitments. Jurisdictional notes highlight privacy, accessibility, and sector-specific regulations relevant to your context. Designed for organizations that develop or use AI, from startups to the enterprise and public sector.

What you’ll learn

• Translate ISO/IEC 42001 into an AIMS roadmap

• Define scope, policy, roles, and governance structure

• Run AI risk/impact assessments (bias, safety, privacy, security)

• Implement lifecycle controls: data, design, testing, deployment, change

• Establish monitoring, incident response, and model drift management

• Manage third-party models, data providers, and contracts

• Design transparency, human oversight, and recordkeeping

• Prepare for internal audits, management reviews, and improvement

Who should attend

• AI/ML leaders, product owners, and data science managers

• Risk, compliance, privacy, and information security teams

• Quality/IMS managers integrating AI governance

• Engineering and platform (MLOps) leaders

• Executives accountable for AI strategy and ethics

Recommended

• Basic ISO/PDCA or governance/risk knowledge

• Familiarity with AI/ML concepts and data pipelines

• Awareness of privacy/security frameworks (helpful)

• Experience with software lifecycle or vendor management (helpful)