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Computing and Information Technology

Live Online Professional AI Governance, Responsible AI & ISO 42001 Training Course

Live online, instructor-led · next cohort Oct 26, 2026 · from USD 1,700

Organisations are deploying machine learning, chatbots and generative AI faster than they can govern them, and boards, regulators, customers and donors are asking who is accountable when a model gets it wrong. Experienced practitioners who can turn principles into controls are in short supply. Ten days give you the depth to build an AI management system rather than a policy that sits unread.

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At a Glance

How Live Online Training Works

Live online training, led by a trainer in real time, for participants anywhere.

More about live online training →
Format
Live online, instructor-led
Duration
Mon - Fri (10 Days)
Fee
USD 1,700 (KES 160,000)
Next start dates
Oct 26, 2026, Nov 23, 2026, Dec 21, 2026
Certificate
Certificate of Completion
What you need
A computer with a reliable internet connection, a webcam and a headset

About this course

Artificial intelligence now influences credit decisions, hiring, diagnosis, fraud detection, citizen services and customer conversations. With that reach come new exposures: biased outcomes, opaque decisions, leaked data, hallucinated advice and dependence on third-party models that the organisation does not control. Regulation is emerging in many jurisdictions, and large buyers increasingly ask suppliers for evidence of AI governance.

The Professional AI Governance, Responsible AI & ISO 42001 Training Course is a ten-day programme for practitioners who must design, operate or assure that governance. The first half builds the foundations: how AI systems are built and fail, how to categorise risk, how to apply responsible AI principles to real use cases and how to organise roles, committees and policies. The second half focuses on the management system standard ISO/IEC 42001, showing how to scope an AI management system, perform AI impact assessments, implement controls, monitor performance and prepare for internal and external audit.

Participants work throughout on a case organisation, producing the artefacts an auditor would expect to see. By the end they have a tested set of documents, a risk register and a phased implementation plan, as well as the confidence to explain governance choices to technical teams and executives alike.

Training Objectives

After the ten days, participants will be able to:

  • Describe the AI lifecycle and the risks that arise at each stage.
  • Apply responsible AI principles of fairness, transparency, accountability and safety to specific use cases.
  • Compare the NIST AI RMF, OECD principles, the EU AI Act and ISO/IEC 42001.
  • Create and maintain an inventory of AI systems with risk classification.
  • Conduct AI impact and bias assessments and document mitigation.
  • Draft an AI policy, roles and committee structure suited to their organisation.
  • Interpret ISO/IEC 42001 clauses and Annex A controls and plan their implementation.
  • Assess third-party AI suppliers and plan internal audits ahead of certification.

What you'll learn

Describe the AI lifecycle and the risks that arise at each stage.
Apply responsible AI principles of fairness, transparency, accountability and safety to specific use cases.
Compare the NIST AI RMF, OECD principles, the EU AI Act and ISO/IEC 42001.
Create and maintain an inventory of AI systems with risk classification.
Conduct AI impact and bias assessments and document mitigation.
Draft an AI policy, roles and committee structure suited to their organisation.
Interpret ISO/IEC 42001 clauses and Annex A controls and plan their implementation.
Assess third-party AI suppliers and plan internal audits ahead of certification.

Key Takeaways

Delegates leave with:

  • An AI system inventory and risk classification template.
  • A completed sample AI impact assessment and model card.
  • A draft AI policy, acceptable use rules for generative AI and a roles matrix.
  • A statement of applicability outline mapped to Annex A controls.
  • An internal audit checklist for an AI management system.
  • A phased roadmap to ISO/IEC 42001 readiness for their organisation.

Training Methodology

The programme is delivered as a working lab around a single case organisation:

  • Short briefings followed immediately by drafting of policies, assessments and registers
  • Hands-on bias testing and model documentation using sample datasets and models
  • Clause-by-clause workshops that produce the documents an auditor would request
  • A mock internal audit with participants acting as auditors and auditees
  • Final roadmap presentations reviewed by facilitators and peers
FAQ

Frequently Asked Questions About Live Online Professional AI Governance, Responsible AI & ISO 42001 Training Course

Everything you need to know about this course before you register.

By the end of the Professional AI Governance, Responsible AI & ISO 42001 programme, you'll be able to describe the ai lifecycle and the risks that arise at each stage, apply responsible ai principles of fairness, transparency, accountability and safety to specific use cases, compare the nist ai rmf, oecd principles, the eu ai act and iso/iec 42001, and create and maintain an inventory of ai systems with risk classification. The full breakdown of topics is covered session by session in the Course Outline tab above.

Still have questions about Live Online Professional AI Governance, Responsible AI & ISO 42001 Training Course? Chat with an advisor·Visit the full FAQ

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What Our Clients Say

VRG brings strategic discipline to complex organizational challenges. Their approach is structured, data-driven, and outcome-focused.

Levis Wabwire

Levis Wabwire

Managing Director

They facilitated our strategy review, we improved departmental KPI alignment by 35% and reduced operational bottlenecks significantly.

David Oketch

David Oketch

Strategy Lead

Employee engagement scores increased following the leadership training program. The difference in accountability culture is evident.

Wendy Albright

Wendy Albright

Program Manager

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