As AI use spreads from a handful of pilots to dozens of models, chatbots and vendor features, the governance function faces a volume problem. Manual reviews, emailed spreadsheets and committees that meet once a month cannot keep pace, and the result is either a queue that frustrates delivery teams or a process that is quietly bypassed. Neither outcome satisfies regulators, auditors or the people affected by automated decisions.

The Operational Excellence in AI Governance, Responsible AI & ISO 42001 Training Course applies process improvement disciplines to the oversight of AI. The first five days treat the AI management system as a set of processes to be mapped, measured and standardised: lifecycle value streams, intake and triage, proportionate review paths, documented procedures and performance metrics aligned with the requirements of the standard. The second five days go deeper into operating at scale, with controls built into machine learning pipelines, production monitoring, incident and change management, supplier operations and an audit approach that samples efficiently. The programme closes with an integrated project in which each participant redesigns the governance operating model of a case organisation.

Delivery mixes process mapping workshops, metric design clinics, pipeline walkthroughs and incident simulations, so that participants work through both the governance and the engineering sides of the problem. Lean and Six Sigma tools are introduced where they help, without assuming prior training in either.

Through the ten days, participants will learn to:

• Map the end-to-end AI governance value stream and identify delays, rework and duplicated reviews.
• Design risk-tiered intake and triage so that review effort matches the impact of each AI system.
• Standardise governance procedures, templates and decision rights using RACI charts and controlled documentation.
• Define KPIs, key risk indicators and AI objectives that meet the performance evaluation requirements of ISO/IEC 42001.
• Integrate policy checks, approvals and evidence capture into MLOps and CI/CD pipelines.
• Operate production monitoring, incident response and change control for AI systems.
• Apply root cause analysis and corrective action to recurring governance failures.
• Plan efficient internal audits and management reviews that drive continual improvement.

The programme suits those who run or improve AI oversight day to day, for example:

• Heads of AI governance and responsible AI programme managers
• Model risk and operational risk managers
• MLOps, platform and machine learning engineers
• Chief data officers and data governance managers
• Compliance and data protection leads who sign off AI use cases
• Lean and Six Sigma practitioners supporting technology functions
• ISO management system and quality managers
• Internal and IT auditors planning AI assurance work
• Shared services and digital delivery managers in government agencies and development organisations

Each participant returns to work with:

• A current-state and future-state map of an AI governance value stream.
• A triage decision tree with target turnaround times for each risk tier.
• A RACI chart and procedure set for intake, approval, change and retirement of AI systems.
• A governance dashboard specification with KPIs, key risk indicators and thresholds.
• A pipeline control design showing which checks run automatically and which need human sign-off.
• An AI incident runbook with severity levels, escalation routes and post-incident review steps.
• A redesigned operating model and 90-day improvement plan for a case organisation.

Learning follows the way process improvement teams actually work. Methods include:

• Process mapping workshops using swimlanes and value stream maps on a shared case
• Metric design clinics where groups build and stress-test governance dashboards
• Walkthroughs of a sample MLOps pipeline showing where automated gates sit
• Incident simulations with injected events and timed escalation decisions
• Root cause analysis exercises on recurring governance failures
• An operating model project presented to a mock executive panel

On attending all ten days and completing the mapping workshops, simulations and final operating model project, participants receive a CPD-accredited Certificate of Completion issued by Vision Reach Global Consultancy.

It documents professional training. Certification of an AI management system against ISO/IEC 42001 is a separate process, carried out for organisations by certification bodies.