AI Project Governance Framework Practitioner

You’ll learn how to apply the AIPGF Capability Maturity Model (CMM) to assess the maturity of AI governance practices across your organisation. This includes analysing your current state, identifying areas for improvement, and developing a practical roadmap for progress. The course focuses on consistency and scalability, helping you build governance structures that evolve with organisational needs while remaining aligned with strategic objectives, risk appetite, and delivery pace.

The course explores how to apply AIPGF within complex, real-world delivery environments. You’ll discover how to scale and adapt governance activities based on factors like project size, complexity, business sector and regulatory context. It also shows you how to align AI governance with traditional methods like PRINCE2®, MSP®, or Agile, ensuring that governance enhances rather than obstructs delivery. Case-based learning helps you put these techniques into practice, preparing you to tailor governance in dynamic and fast-moving project scenarios.

Effective governance starts with clarity in roles. This part of the course covers how to define, assign, and in some cases combine responsibilities for AI governance. You’ll review the framework’s model for identifying key stakeholders, from sponsors and project managers to assurance leads and governance boards. You’ll also explore how to ensure each role has clear responsibilities, appropriate authority, and access to the information they need to ensure accountability and compliance.

You’ll explore how to navigate ethical and legal challenges when implementing AI solutions in projects and programmes. The course helps you understand how to build governance that enables responsible decision-making while also responding to organisational and societal concerns about AI use. You’ll cover techniques to manage resistance to AI, build confidence across teams, and champion transparent, fair and auditable AI adoption that stands up to scrutiny.