Artificial intelligence now supports credit decisions, recruitment, fraud detection, citizen services, diagnostics and customer chat. Each use brings questions about accuracy, bias, explainability, privacy and accountability, and regulators, investors and customers increasingly expect organisations to show how those questions are answered. Ad hoc controls scattered across IT, legal and data teams rarely stand up to that scrutiny.

This programme teaches managers how to build AI governance as a coherent management system. The first week establishes foundations: the AI lifecycle, responsible AI principles, the structure of ISO/IEC 42001, organisational context, leadership commitment, policy and objectives, and a practical method for inventorying and risk-rating AI use cases. The second week concentrates on operating the system. Participants study data governance, model development and validation standards, bias and robustness testing, generative AI risks, human oversight, monitoring and incident response, supplier management, competence and awareness, internal audit and management review.

The learning approach is hands-on. Participants draft policies, complete an impact assessment, test a risk register and assemble a documentation pack for a chosen AI system. By the end they have a roadmap for certification readiness and a clear view of the governance resources their organisation needs.

By the end of the programme, participants will be able to:

• Explain responsible AI principles and how they translate into management controls.
• Interpret the clauses and Annex controls of ISO/IEC 42001 for their organisation.
• Establish AI governance structures, roles and accountability, including board oversight.
• Build an AI inventory and classify use cases by risk and impact.
• Conduct AI risk assessments and impact assessments covering bias, privacy and safety.
• Set requirements for data quality, model validation, monitoring and human oversight.
• Manage generative AI risks and third-party AI suppliers.
• Plan internal audits, corrective actions and management reviews for an AI management system.

The programme is intended for those responsible for how AI is adopted, controlled and assured, including:

• Chief information, data and technology officers
• Heads of risk, compliance and legal affairs
• Data science and AI team leads
• Internal and external auditors
• Information security and privacy managers
• Product owners and digital transformation leaders
• Public sector ICT directors and policy officers
• Quality managers extending management systems to AI
• Consultants advising on AI governance

Participants leave the programme with:

• A draft AI policy and governance charter for their organisation.
• An AI system inventory template and risk classification method.
• A completed AI impact assessment for a chosen use case.
• A gap assessment against ISO/IEC 42001 with a prioritised action plan.
• Model validation and monitoring checklists for operational teams.
• An internal audit programme and management review agenda.

The ten days alternate between concept sessions and working labs so that governance becomes practical. Participants will experience:

• Expert-led walkthroughs of standard clauses with plain-language interpretation
• Drafting labs for policy, inventory, risk register and impact assessment
• Case studies of AI failures and how controls would have changed the outcome
• Mock internal audit with evidence review and findings reporting
• An integrated project built around a real or simulated AI system

On meeting attendance requirements and completing the practical exercises and integrated project, participants receive a CPD-accredited Certificate of Completion from Vision Reach Global Consultancy.

The certificate recognises the training undertaken. It is not a certification to ISO/IEC 42001, which is awarded to organisations by accredited certification bodies.