What AI adoption really means

Most organisations are “using AI” somewhere now.

A pilot. A chatbot. A meeting note summariser. A handful of people experimenting in private.

That is not adoption.

Adoption is a change in work

Adoption shows up when people change how they work, not just which tool they click.

It’s visible in the workflow: decisions are made differently, handovers are redesigned, and time moves from repetition to judgement.

Pilots don’t fail because the model is weak

Most pilots stall because the surrounding system stays the same.

The work still begins in the same place, gets reviewed in the same way, and ends with the same accountability.

So the “AI bit” becomes a novelty layer, not a new operating rhythm.

Three tests for real adoption

1) A problem only AI makes feasible. Start where AI is the difference, not a like for like automation. Pick one process that was too messy, too slow, or too expensive before.

2) Guardrails before fireworks. Clarity beats policy theatre. Define what’s allowed, what’s not, and how people should check outputs. Make it easy to do the right thing.

3) A measurable change in the workflow. Track cycle time, quality, and decisions improved. Don’t track “prompts used”. Track outcomes.

The simplest adoption metric

If the tool disappeared tomorrow, would the team keep the new way of working?

If the answer is no, it was usage, not adoption.