About Certificate in AI Governance
This course gives governance, compliance, risk, and technology professionals a complete framework for leading AI governance within their organisation. AI governance has moved from a nice-to-have into a board-level responsibility, and this course covers the full scope of what that requires — from ethics principles and regulation through to risk management, Shadow AI oversight, and enterprise strategy.
You'll start with the foundations of AI governance and ethics, then move into the global regulatory landscape and compliance obligations for high-risk AI systems. From there, the course covers AI risk management, bias detection, and explainability, followed by designing governance frameworks that include often-overlooked Shadow AI, and finishing with how to build an enterprise-wide AI governance strategy and maturity roadmap.
By the end, you'll complete a capstone exercise designing a full AI governance blueprint for your own organisation, backed by certification.
Expected Outcomes
The course is structured around five stages — from AI governance foundations through to enterprise strategy — so each skill builds toward a complete governance capability. By the end, you'll be able to:
- Explain AI governance principles including fairness, accountability, transparency, and privacy
- Navigate global AI regulations and conduct regulatory impact assessments
- Apply compliance frameworks for high-risk AI systems, including documentation and reporting
- Identify and assess AI risks and apply bias detection and mitigation strategies
- Apply Explainable AI methods and manage the AI model lifecycle
- Design governance structures, including committees, roles, and accountability models
- Govern Shadow AI and integrate oversight into existing governance frameworks
- Develop an enterprise AI governance strategy and complete governance blueprint
Training Method
The course begins with the foundations of AI governance and ethics, using real governance failure case studies to ground the concepts in practice, before moving into the global regulatory landscape and compliance requirements for high-risk AI systems, including a regulatory impact assessment workshop.
From there, you'll work through AI risk management, bias detection, and explainability through hands-on risk assessment workshops, followed by designing governance frameworks that specifically address Shadow AI — the AI tools used within organisations outside formal oversight. The course closes with strategy and maturity development, culminating in a capstone exercise where you design a complete, organisation-specific AI governance blueprint as part of your certification assessment.
