AI Governance and Ethics

Course objectives

On completion of this programme, you should be able to:

1. Understand the responsibilities of governing bodies and executive management for AI oversight.
2. Establish an appropriate AI governance and accountability structure.
3. Identify ethical, legal, operational, data and reputational risks arising from AI.
4. Apply ethical principles to AI design, acquisition, implementation and use.
5. Develop an AI inventory and classify AI applications according to their risk.
6. Evaluate bias, transparency, explainability, privacy and human oversight.
7. Align AI governance with organisational strategy, risk management and assurance.
8. Develop practical governance reports and dashboards for decision-makers.

Course format

Face-to-face and live online attendance.

The programme combines governance principles, practical examples, facilitated discussions, case studies and implementation tools. Participants will examine how AI affects decision-making, accountability, stakeholder trust and organisational performance.

Best-practice frameworks

ISO/IEC 42001 | NIST AI Risk Management Framework | King governance principles | COSO | COBIT | ISO 31000 | Three Lines Model | POPIA | Responsible AI principles

Duration

Two days.

Participants attending the complete programme will receive a certificate of attendance reflecting the applicable continuing professional development hours.

Course outcomes

1. Strengthen AI governance
   Establish clear governance structures, decision rights, reporting arrangements and accountability for AI.
2. Promote ethical AI use
   Apply fairness, transparency, explainability, privacy, human oversight and stakeholder inclusivity to AI-related decisions.
3. Manage AI risk
   Identify and assess strategic, operational, legal, ethical, data, cybersecurity, third-party and reputational risks.
4. Establish an AI management system
   Understand the policies, processes, responsibilities and evidence required to manage AI consistently.
5. Improve governing-body oversight
   Develop meaningful AI governance reports and dashboards for governing bodies and oversight committees.
6. Integrate the Three Lines
   Clarify the responsibilities of management, risk and compliance functions, internal audit and external assurance providers.
7. Evaluate AI controls
   Assess whether controls over data, models, access, testing, monitoring, change management and human intervention are appropriately designed and operating effectively.
8. Develop an implementation roadmap
   Prioritise the practical actions required to strengthen AI governance and ethics within the participant’s organisation.

Presenter

Deon van der Westhuizen

Deon specialises in governance, risk management, internal audit, organisational leadership and AI governance. His programmes focus on translating governance frameworks into practical tools that can be applied by governing bodies, executives and assurance professionals.

Recent clients

Recent clients include:

• South African Revenue Service
• PPS
• KMES
• University of Cape Town
• Ministry of Energy, Saudi Arabia