CONTEXT

AI adoption lacked structure and shared understanding

As AI became more present in day to day work, there was a clear gap between interest and capability. Teams were experimenting, but there was no consistent way to define what good looked like, how skills should develop, or how to assess maturity across roles.

CHALLENGE

Define AI capability in a practical and usable way

The challenge was to create something that was structured but not heavy. It needed to work across different roles, avoid technical jargon, and help people understand where they are today and how they can improve. Most frameworks are either too abstract or too complex to use in practice.

APPROACH

Designing a clear and structured competency model

I designed the AI Competency Framework as a practical model that breaks AI capability into clear areas and levels. It focuses on real behaviour, not theory. The framework defines what capability looks like across understanding, application, and thinking, and allows individuals and teams to assess and improve in a structured way.

OUTCOME

A usable framework to guide AI capability growth

The result is a framework that can be used to assess current capability, guide learning, and support adoption. It helps individuals understand how to use AI more effectively and gives organisations a clearer way to build capability over time.