| Date | Venue | Duration | |
|---|---|---|---|
| 26 - 30 October 2026 | Sandton, Gauteng | 5 Days | |
| 07 - 11 December 2026 | Sandton, Gauteng | 5 Days |
Please note: This is not a final registration, one of our team members will contact you shortly to finalise your registration.
As organisations adopt AI more widely, governing its use responsibly has become a board-level concern, not just a technical one. This AI Governance, Ethics and Responsible AI course builds practical frameworks for AI governance, ethical use, data privacy, and risk management — equipping participants to establish policies and oversight structures that allow their organisation to adopt AI confidently and defensibly.
The regulatory landscape is moving fast: the EU AI Act’s enforcement for high-risk systems begins in 2026, carrying penalties of up to €35 million or 7% of global turnover, while ISO/IEC 42001 has emerged as the first certifiable international AI management system standard and the NIST AI Risk Management Framework as the de facto US benchmark. This AI Governance, Ethics and Responsible AI course treats these as a layered governance architecture organisations need to satisfy together, not separate compliance exercises. Case-study driven, using real-world AI governance failures and near-misses as discussion anchors, you’ll leave with a draft AI governance policy framework built for your own organisation.
This AI Governance, Ethics and Responsible AI course equips you to design, implement, and defend AI governance frameworks that satisfy global regulatory expectations while remaining proportionate to your organisation’s scale and risk appetite.
By the end of this AI Governance, Ethics and Responsible AI course, you’ll be able to:
Regulatory Clarity in a Moving Landscape: Understand how the EU AI Act, ISO 42001, and NIST AI RMF fit together, instead of treating each as a separate compliance exercise.
Defensible AI Adoption: Build oversight structures that let your organisation adopt AI confidently, not fearfully.
Real Risk Recognition: Identify bias, transparency, and accountability risks before they become incidents or headlines.
Privacy-Ready Governance: Apply data privacy principles specific to AI systems and training data, not generic data protection theory.
A Policy You Can Actually Use: Leave with a draft AI governance policy tailored to your organisation’s scale and risk appetite.
This AI Governance, Ethics and Responsible AI course is designed for:
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.
Module 1: Foundations of AI Governance
Why AI requires distinct oversight from traditional IT governance
The board-level shift: AI governance as a strategic, not purely technical, concern
Core principles of responsible AI: fairness, accountability, transparency, and safety
Building the business case for proactive AI governance
Practical Exercise: Map your organisation’s current AI governance gaps against core governance principles.
Module 2: The Global AI Regulatory Landscape
The EU AI Act: risk-based obligations, enforcement timeline, and penalties
ISO/IEC 42001 as a certifiable AI management system standard
The NIST AI Risk Management Framework and its role in US and global practice
Using the three frameworks together as a layered governance architecture, not competing alternatives
Practical Exercise: Map which regulatory frameworks apply to your organisation’s AI use, and identify overlapping requirements.
Module 3: Ethical Risks in AI
Identifying bias in AI systems and its business and reputational consequences
Fairness considerations across different AI use cases
Transparency and explainability: what stakeholders are entitled to know
Accountability structures when AI systems cause harm or error
Practical Exercise: Assess a sample AI use case for bias, fairness, and transparency risks.
Module 4: Data Privacy and Protection in AI Systems
Privacy considerations specific to training data and model inputs
Consent and data subject rights in AI-driven decision-making
Cross-border data transfer considerations for AI systems
Common data privacy failures in AI deployments and how to avoid them
Practical Exercise: Review a sample AI system for data privacy compliance gaps.
Module 5: Designing AI Oversight Structures
Structuring approval processes for new AI initiatives
Defining roles and responsibilities across risk, compliance, and business functions
Setting escalation pathways for high-risk AI decisions
Embedding AI oversight into existing governance structures rather than building from scratch
Practical Exercise: Design an approval workflow for a new AI initiative at your organisation.
Module 6: Risk Tiering and Ongoing Monitoring
Applying a risk-based tiering approach to AI use cases
Setting monitoring requirements proportional to risk tier
Post-deployment monitoring and incident reporting practices
Keeping governance proportionate as AI use scales across the organisation
Practical Exercise: Build a risk tiering matrix and assign monitoring requirements to a set of sample AI use cases.
Module 7: Building an AI Governance Policy — Capstone Exercise
Structuring a complete AI governance policy document
Tailoring policy scope and rigour to organisational size and risk appetite
Presenting a governance policy for leadership sign-off
Planning for policy review and updates as regulation and technology evolve
Practical Exercise: Draft an AI governance policy framework tailored to your own organisation.
Governance Lens: Relevant South African Requirements
Delegates apply the following requirements proportionately to the selected use case. This is an implementation lens, not legal advice; sector-specific obligations must still be confirmed by the organisation.
POPIA (Act 4 of 2013)
Why it matters: Personal information used for prompting, training, decisions, reporting or retrieval must be lawfully and securely processed.
Control designed in class: Data minimisation, permission checks, confidentiality, retention and human approval rules.
Cybercrimes Act 19 of 2020
Why it matters: AI-enabled workflows can increase exposure to unauthorised access, data misuse or harmful disclosure.
Control designed in class: Access boundaries, incident escalation, secure use rules and logging expectations.
ECTA (Act 25 of 2002)
Why it matters: Digital records and electronic transactions require sound integrity and control practices.
Control designed in class: Verification, version control, sign-off and evidence retention for AI-assisted outputs.
Employment / Sector Regulation
Why it matters: High-impact use cases in hiring, lending, insurance, procurement or public services require additional fairness and accountability checks.
Control designed in class: Use-case-specific red flags, human decision ownership and legal review gates.
AI Policy Development
Why it matters: South Africa has an AI policy framework; the 2026 draft policy was withdrawn and is not enacted AI law.
Control designed in class: Monitor policy developments without presenting draft material as mandatory law.
Discover how our courses enhance professionals’ effectiveness in their workplaces.
The Training was almost excellent and has now contributed in shaping my career and job prospects for the better.
The facilitator was very passionate and course outline was much relevant for my designation at work and for my personal enhancement.
The Facilitator was good and very professional, he outlined the course very well. A very good Job on his part
Very interesting and interactive programme which is needed in the financial industry.
Discover how our courses enhance professionals’ effectiveness in their workplaces.
Discover more insights on AI, leadership, digital transformation, and professional development.
Fill in your details and we will send the brochure to your email.
Please check your email for confirmation.
Please check your email for confirmation
