AI Project Governance Framework Foundation & Practitioner

Learn how the AI Project Governance Framework is structured and how its lifecycle stages, principles and terminology fit together. This certification provides an easily applicable model you can use to move AI governance from a broad policy concern into day-to-day project activity, with clearer checkpoints and evidence of control. 

AI can affect project decisions in ways that are difficult to explain or challenge. You’ll examine areas such as transparency, bias, explainability and legal responsibility, so you can recognise where extra scrutiny is needed and help teams make decisions that are easier to justify to stakeholders. 

For effective AI project governance, it’s vital that team responsibilities are clearly communicated. You’ll look at how sponsors, steering groups, PMOs, delivery teams, AI specialists and compliance functions contribute to oversight, helping you reduce duplicated effort and uncertainty around who should approve, challenge or monitor AI-related activity. 

Learn how maturity assessment can help organisations understand how well their current governance approach supports AI use. You’ll consider how to adapt the framework to different levels of complexity and risk, giving you a basis for prioritising improvements rather than applying the same controls to every project. 

Understand how clear decision-making processes help AI-enabled projects move forward without weakening control. You’ll examine where approval and escalation responsibilities should sit across the team and associated stakeholders. This helps you recognise when decisions need additional scrutiny, when issues should be escalated, and how clearer accountability can reduce uncertainty.