Management of AI Governance, Responsible AI & ISO 42001 Training Course in Kigali, Rwanda
Classroom training in Kigali · next cohort Oct 26, 2026 · from USD 3,800
Organisations are adopting machine learning and generative AI faster than they are putting controls around them, leaving exposure to biased decisions, leaked data, unreliable outputs and regulatory scrutiny. Managers who can govern AI make it safe to scale. This ten-day programme teaches you to design and operate an AI management system aligned with ISO/IEC 42001, drawing on the NIST AI Risk Management Framework and the principles of fairness, transparency, accountability, safety and privacy. You write AI policy, build an inventory of systems, classify use cases by risk, run impact assessments, and define roles for boards, committees and model owners.
The second week moves into operations: data quality, model validation, monitoring for drift, human oversight, incident handling, generative AI guardrails, third-party and vendor assurance, and internal audit against the standard. Chief information and risk officers, compliance and legal managers, data and AI leaders, internal auditors, product owners and public sector digital leads will gain the most. Delivery is classroom, online or in-house. You complete an integrated project that produces a draft management system pack and readiness gap assessment. A CPD-accredited Certificate of Completion is issued by Vision Reach Global Consultancy.
At a Glance
Training in Kigali, Rwanda
Kigali is Rwanda's clean, safe and well-connected capital, and one of Africa's leading conference cities.
More about training in Kigali →- Format
- Classroom, in Kigali
- Duration
- Mon - Fri (10 Days)
- Fee
- USD 3,800
- Next start dates
- Oct 26, 2026, Nov 23, 2026, Dec 21, 2026
- Certificate
- Certificate of Completion
- Airport
- Kigali International (KGL), about 10 km from the city centre
- Time zone
- Central Africa Time (UTC+2)
- Currency
- Rwandan franc (RWF). Fees are listed in USD.
- Business districts
- Kigali CBD, Kimihurura and Kacyiru
About this course
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.
Training Objectives
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.
What you'll learn
Key Takeaways
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.
Training Methodology
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
Day 1: The AI Landscape and Governance Imperative
- AI, machine learning and generative AI explained for managers
- Incidents and harms: bias, hallucination, data leakage and misuse
- Regulatory and standards landscape for AI
- Responsible AI principles and ethics frameworks
- Why a management system approach works
Day 2: Introduction to ISO/IEC 42001
- Structure, scope and terminology of the standard
- Relationship to ISO 27001, ISO 9001 and ISO 27701
- Plan-Do-Check-Act applied to AI
- Annex controls overview
- Certification process and what auditors look for
Day 3: Context, Leadership and Policy
- Understanding organisational context and interested parties
- Scoping the AI management system
- Leadership commitment and board responsibilities
- Writing an AI policy and objectives
- Roles: AI governance committee, model owners and ethics reviewers
- Exercise: drafting an AI policy
Day 4: AI Inventory and Risk Assessment
- Building an AI system inventory
- Classifying use cases by risk and criticality
- Risk assessment methods and the NIST AI RMF functions
- Risk treatment and acceptance
- Exercise: populating a risk register
Day 5: AI Impact Assessment
- Assessing impact on individuals, groups and society
- Fairness, bias and discrimination analysis
- Transparency and explainability requirements
- Privacy, consent and data protection links
- Documenting and approving an impact assessment
- Workshop: impact assessment for a credit or recruitment tool
Day 6: Data and Model Lifecycle Controls
- Data governance: provenance, quality, labelling and consent
- Development standards, documentation and model cards
- Validation, testing and acceptance criteria
- Robustness, security and adversarial threats
- Change management and version control
Day 7: Deployment, Monitoring and Human Oversight
- Deployment approvals and release gates
- Designing meaningful human oversight
- Performance, drift and fairness monitoring
- Incident detection, escalation and response
- Decommissioning and record retention
- Lab: building a monitoring dashboard specification
Day 8: Generative AI and Third-Party Risk
- Generative AI risks: hallucination, intellectual property and confidentiality
- Acceptable use policies and staff guidance
- Prompt, output and content controls
- Supplier due diligence and contract clauses for AI services
- Managing open-source and embedded AI components
Day 9: Competence, Audit and Continual Improvement
- Competence, training and awareness programmes
- Documented information and evidence management
- Planning and conducting internal audits
- Nonconformity, corrective action and improvement
- Management review inputs and outputs
- Audit practice on sample evidence
Day 10: Integrated Project and Certification Readiness
- Assembling the management system documentation pack
- Gap assessment against the standard
- Building the implementation roadmap, budget and resourcing case
- Preparing for a certification audit
- Group presentations and peer challenge
- Course review and personal action plans
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
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.
Choose Where You Want to Learn
Management of AI Governance, Responsible AI & ISO 42001 Training Course Venues
RwandaKigaliNext Oct 26· 14 dates$3,800Viewing
KenyaNairobiNext Nov 9· 13 dates$3,000- KenyaMombasaNext Oct 26· 14 dates$3,200
- KenyaNaivashaNext Nov 2· 13 dates$3,000
- KenyaKisumuNext Oct 26· 14 dates$3,000
- KenyaMachakosNext Nov 2· 13 dates$3,200
UgandaKampalaNext Nov 2· 13 dates$3,800
TanzaniaArushaNext Nov 9· 13 dates$3,800- TanzaniaDodomaNext Oct 26· 14 dates$3,600
- TanzaniaDar es SalaamNext Oct 26· 14 dates$4,000
- TanzaniaZanzibarNext Nov 16· 13 dates$5,200
NigeriaLagosNext Nov 16· 13 dates$5,600- NigeriaAbujaNext Nov 9· 13 dates$5,600
South AfricaPretoriaNext Nov 2· 13 dates$6,400- South AfricaJohannesburgNext Nov 2· 13 dates$6,800
- South AfricaCape TownNext Oct 26· 14 dates$7,600
UAEDubaiNext Oct 26· 14 dates$7,600
GhanaAccraNext Nov 16· 13 dates$9,000
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Frequently Asked Questions About Management of AI Governance, Responsible AI & ISO 42001 Training Course in Kigali
Everything you need to know about this course before you register.
Management of AI Governance, Responsible AI & ISO 42001 Training Course runs as classroom training in Kigali, Rwanda, in Monday-to-Friday cohorts that start every four weeks. The venue, daily timings and joining details are sent in your Joining Instructions email ahead of the start date.
The next Kigali cohort starts on October 26, 2026, and a new intake follows every four weeks. Pick a date under "Upcoming sessions in Kigali" above and click Register; your seat is confirmed once payment or a signed purchase order is received.
The classroom fee for Management of AI Governance, Responsible AI & ISO 42001 Training Course in Kigali is USD 3,800 per delegate, covering tuition and course materials. Register 3 or more delegates together and a 5% team discount is applied automatically.
Kigali is the only classroom city for Management of AI Governance, Responsible AI & ISO 42001 Training Course in Rwanda at the moment. You can also join a live online cohort from anywhere in Rwanda, or book it in-house at your organisation's own premises.
Yes — Management of AI Governance, Responsible AI & ISO 42001 Training Course can be delivered at your offices in Kigali or at a venue you choose, on dates that suit your team, with case studies tailored to your sector. Message our training advisors to request a proposal.
By the end of the Management of AI Governance, Responsible AI & ISO 42001 programme, you'll 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, and build an ai inventory and classify use cases by risk and impact. The full breakdown of topics is covered session by session in the Course Outline tab above.
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, and Consultants advising on AI governance.
Management of AI Governance, Responsible AI & ISO 42001 Training Course typically runs as 10 Days. It's available as in-person classroom, live virtual, and in-house corporate training — every course can also be delivered on-site for your team on dates that suit you.
Yes — delegates who meet the attendance requirement receive a Certificate of Completion for Management of AI Governance, Responsible AI & ISO 42001 Training Course from Vision Reach Global Consultancy, issued in the name you register with, so double-check the spelling at checkout.
Management of AI Governance, Responsible AI & ISO 42001 Training Course is pitched at advanced professionals. If you're unsure whether it's the right fit for your current role or background, message our training advisors before you register and they'll help you confirm.
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