The forces behind your AI adoption
Seven forces that hold AI adoption in place
They are documented by Kahneman, Cialdini and Thaler. They apply to your newest hire and to your most senior director. And they are all designable. As long as you leave them untouched, every AI rollout evaporates a few months after launch.
01 - The tool-first illusion
IT can roll out software. It can't fix behaviour
The question lands with IT because AI looks like a technology problem. But IT can't fix fear, break a habit or protect someone's status. The licence is ready. The people aren't.
02 - The search-engine model
Typing a question and closing the tab isn't AI use
Someone types a question, reads the answer, closes the tab: the same behaviour as googling, just with a different tool. The mental model is wrong, and it shows in every result.
03 - Status threat
The fear nobody says out loud
Nobody admits "I'm afraid AI will show I don't know this" in a meeting. But plenty of people think it, and that fear steers what they do every single day.
04 - The craftsmanship myth
The best prompt rarely comes from the best prompter
Everyone learns to prompt. But the sharpest results come from people who already know their craft inside out. Without that depth, AI has nothing to work with.
05 - Social norms
People do what they see colleagues do
If nobody visibly uses AI in a meeting or a document, it never becomes the norm, whatever the onboarding deck promised.
06 - Defaults
The default decides what most people do
If AI isn't the standard first step in a workflow or a template, most people never reach for it on their own.
07 - System 1
96% of behaviour is automatic
Most AI programmes appeal to conscious, rational thinking. But daily work runs on autopilot, and the old habit wins from any tool that requires a deliberate switch.
