Strategy and Innovation in AI Governance, Responsible AI & ISO 42001 Training Course

Artificial intelligence has moved from pilot projects into credit decisions, customer service, recruitment, medical triage, fraud detection and public services, and generative AI has put powerful tools in the hands of every employee. At the same time, the publication of ISO/IEC 42001 in 2023, the adoption of the EU AI Act and guidance such as the NIST framework have set clear expectations for how organisations should govern AI. Leaders now face a strategic question: how to capture the value of AI quickly without exposing the organisation to bias, privacy breaches, security failures, intellectual property disputes or loss of public trust.

The Strategy and Innovation in AI Governance, Responsible AI & ISO 42001 Training Course answers that question over ten days. The first week builds the strategic and structural foundations: AI strategy and value, use-case portfolio management, responsible AI principles, the regulatory landscape, and the requirements of an AI management system, including scope, AI policy, roles, risk assessment, impact assessment and the Statement of Applicability. The second week goes deeper into innovation under control, covering generative AI governance, sandboxes and staged release, third-party and foundation model risk, technical assurance for fairness, robustness and explainability, internal audit of the management system, and an integrated capstone in which teams design a governance operating model for a realistic organisation.

Teaching combines strategy workshops, policy drafting, structured assessment labs and peer critique, so participants leave with documents they can adapt immediately.

On completion of the ten days, participants will be able to:

• Align an AI strategy and use-case portfolio with organisational objectives, risk appetite and responsible AI principles.
• Interpret the requirements of ISO/IEC 42001 and plan the scope, policy, roles and controls of an AI management system.
• Apply the NIST AI RMF and ISO/IEC 23894 to identify, analyse and treat AI risks across the system lifecycle.
• Conduct AI system impact assessments that consider individuals, groups and society.
• Classify AI use cases against the EU AI Act risk tiers and comparable national and regional approaches.
• Design governance for generative AI, including acceptable use rules, sandboxes and staged release.
• Evaluate third-party AI vendors, foundation models and data sources through structured due diligence.
• Establish metrics, monitoring and internal audit arrangements that sustain responsible AI performance.

The programme is aimed at experienced professionals who shape or oversee AI adoption, such as:

• Chief digital, data and analytics officers
• Heads of AI, innovation and digital transformation
• Chief information officers and chief technology officers
• Chief risk officers, compliance heads and model risk managers
• Data science and machine learning team leads
• Information security and privacy leaders, including DPOs and CISOs
• Internal auditors and assurance professionals reviewing AI systems
• Policy makers and regulators working on AI and digital economy strategy
• Product owners and strategy managers in banking, insurance, telecoms, health and the public sector

Over the two weeks, participants assemble a working toolkit that includes:

• An AI use-case portfolio scored for strategic value, feasibility and risk.
• A draft AI policy and responsible AI principles statement ready for board review.
• An ISO/IEC 42001 gap assessment and implementation roadmap.
• An AI risk register and a completed AI system impact assessment for one use case.
• A generative AI acceptable use policy and sandbox operating rules.
• A third-party AI and model due diligence questionnaire.
• A responsible AI metrics dashboard covering fairness, drift, incidents and adoption.
• A governance operating model presented and critiqued in the capstone.

Ten days allow for both strategic debate and detailed practice. Participants learn through:

• Strategy workshops that connect AI governance decisions to business value
• Clause-by-clause analysis of ISO/IEC 42001 with drafting exercises for policies and the Statement of Applicability
• Risk and impact assessment labs on realistic use cases in credit, health and public services
• Sessions with sample model outputs to interpret fairness, explainability and drift results
• Policy and contract review clinics for generative AI and third-party models
• A team capstone presented to a simulated executive committee for challenge and feedback

Participants who attend all ten days and complete the workshop, lab and capstone assignments receive a CPD-accredited Certificate of Completion issued by Vision Reach Global Consultancy.

This is a training certificate, not ISO/IEC 42001 certification of an organisation or a personal auditor credential. The toolkit documents produced during the programme remain with participants as evidence of their applied work.