I use AI every day and was an early and enthusiastic adopter of generative AI.
At first, I was dazzled by what it could do. Work that once took hours could be developed in minutes. Ideas became easier to explore. Research, structure and expression all accelerated.
Then I started questioning my own behaviour.
Was I still thinking as deliberately? Was I challenging the output or being carried by it? Did I understand and own the finished work as fully as I thought I did?
Sometimes AI made my work sharper and more ambitious. Sometimes it made it flatter, safer or more convincing than the thinking behind it.
I began comparing what I was experiencing with emerging research and reported cases. The same questions kept appearing.
The technology was not the whole story. The behaviour forming around it mattered too. That is what I decided to examine.
I have spent more than two decades in senior brand, marketing and consulting roles, working with established organisations and growing businesses.
I have helped organisations clarify what they stand for, understand customers, shape propositions, lead teams and turn plans into work people can actually use.
That experience taught me something simple.
A strategy may be clear. A process may be well designed. A new technology may be genuinely useful.
Performance still depends on the decisions, habits and interactions that form around them.
AI makes that behavioural layer newly important. It also makes it harder to see because the finished output may reveal very little about how the work was framed, questioned, checked or understood.
That is the lens I now bring to AI.
AI may be saving time, improving quality, widening access to expertise or enabling work that was previously difficult to do.
The purpose is to understand those gains alongside the behaviours forming around them.
This is not generic AI training, technical implementation, policy work or employee surveillance.
It is a practical way to see which AI-related behaviours are strengthening performance, identify those that may be getting in the way and introduce changes that can be tested in real work.
I am building the work carefully through focused engagements, evidence from real work and practical interventions that can be reviewed and improved.
The longer-term ambition is to help organisations develop human capabilities that remain valuable as AI becomes more capable.