| Date | Venue | Duration | |
|---|---|---|---|
| 19 - 21 August 2026 | Cape Town | 3 Days | |
| 19 - 21 October 2026 | Cape Town | 3 Days |
Artificial Intelligence is transforming economies across the globe — from advanced digital markets to rapidly developing African economies. However, alongside innovation comes significant governance, ethical, regulatory, and reputational risk.
Governments, regulators, and global institutions such as the ISO, OECD, NIST, and the European Union are introducing AI governance frameworks to ensure responsible deployment. African countries are simultaneously strengthening data protection laws, digital governance frameworks, and public accountability mechanisms.
This intensive 5-day executive programme equips leaders, board members, regulators, and professionals with a globally aligned yet Africa-relevant AI governance framework. Participants will learn how to design AI governance structures, manage ethical and operational risks, comply with emerging regulations, and align AI strategy with organisational sustainability and stakeholder trust.
The AI Governance and Risk Leadership programme combines international best practice with African case studies and practical implementation tools suitable for both public and private sector institutions.
By the end of this AI Governance and Risk Leadership course, participants will be able to:
Explain global AI governance frameworks and their relevance to African markets
Analyse AI-related ethical, operational, legal, and reputational risks
Design and implement an AI governance structure aligned with board-level oversight
Develop ethical AI policies that address bias, transparency, fairness, and accountability
Establish AI risk management processes aligned to ISO, NIST, and OECD standards
Interpret emerging AI regulations and ensure organisational compliance
Create a practical AI governance roadmap tailored to their organisation
This AI Governance and Risk Leadership programme is designed for:
Board Members and Non-Executive Directors
Chief Executive Officers and Executive Management
Chief Financial Officers and Finance Executives
Chief Information Officers (CIOs) and Chief Technology Officers (CTOs)
Risk and Compliance Professionals
Governance, Risk and Compliance (GRC) Practitioners
Regulators and Policy Makers
Legal Advisors and Corporate Counsel
Internal and External Auditors
AI, Data Science, and IT Leaders
Public Sector Executives and State-Owned Entity Officials
Our diverse instructional approaches ensure effective learning:
– Lectures & Presentations: Engage with expert-driven, stimulating content.
– Course Material: Access well-crafted supporting resources.
– Group Work: Collaborate on discussions and case studies for practical insights.
– Workshops & Role-Play: Participate in immersive, scenario-based activities.
– Practical Application: Focus on applying theoretical knowledge in real situations.
– Post-Training Support: Receive extensive support after training for skill implementation.
Day 1: Foundations of AI Governance in a Global Context
Understanding AI and Its Strategic Impact
Overview of Artificial Intelligence and Generative AI
AI applications across industries (finance, public sector, telecoms, mining, health)
Strategic benefits and transformation opportunities
Emerging risks in AI adoption
Governance, Risk and Compliance (GRC) in the AI Era
Corporate governance principles
Board oversight responsibilities for AI
Governance challenges in Generative AI
Integrating AI into enterprise governance frameworks
Day 2: Ethical AI and Responsible Innovation
Global AI Ethical Frameworks
OECD AI Principles
NIST AI Risk Management Framework
ISO AI governance standards
UN and global digital ethics initiatives
Ethical Risks in AI Systems
AI bias and discrimination risks
AI hallucinations and misinformation
Privacy and data protection concerns
Transparency and explainability
Practical Mitigation Techniques
Reducing bias in AI systems
Prompt engineering to reduce hallucinations
Ethical AI policy development
Embedding ethics into AI lifecycle management
Day 3: Designing AI Governance Structures
Establishing an AI Governance Model
AI Governance Committees and Innovation Councils
Mandate, scope, and reporting structures
Membership composition and required competencies
Aligning AI governance with board structures
AI Policy and Control Frameworks
AI acceptable use policies
Accountability and control mechanisms
Monitoring AI system performance
Documentation and audit readiness
Stakeholder Management and Trust
Communicating AI decisions to stakeholders
Managing public trust in AI systems
Responsible AI in emerging economies
Day 4: AI Risk Management and Regulatory Compliance
Identifying and Assessing AI Risks
Strategic, operational, reputational, and legal risks
Risk classification and impact assessment
AI risk registers and control mapping
Regulatory Landscape
EU AI Act overview
African data protection frameworks (POPIA, NDPR, Data Protection Acts)
Cross-border data governance
Sector-specific regulatory concerns (banking, telecoms, public sector)
Building an AI Compliance Framework
AI compliance programme design
Internal controls and assurance
Audit and reporting requirements
Automated monitoring and compliance tools
Day 5: Implementation, Strategy and Future Readiness
AI Governance Implementation Roadmap
Conducting AI governance maturity assessments
Gap analysis and prioritisation
Budgeting and resource allocation
Change management and leadership alignment
Managing AI in Fast-Changing Environments
Continuous monitoring and adaptation
Managing vendor and third-party AI risks
Incident response planning for AI failures
Future Trends in AI Governance
Autonomous AI systems
AI and cybersecurity convergence
African digital transformation strategies
Preparing for next-generation AI regulation
Practical Workshop
Participants develop a draft AI Governance Roadmap for their organisation
Group presentations and expert feedback
Discover how our courses enhance professionals’ effectiveness in their workplaces.
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