Using AI
74%
of frontline employees are now regular AI users
BCG, AI at Work 2026
Measuring the human side of an AI change
We measure the four foundations that decide whether it holds:
Then we work on them, and measure again.
The state of play
Using AI
74%
of frontline employees are now regular AI users
BCG, AI at Work 2026
Seeing a return
7%
of organisations report an established return
KPMG, Global AI Pulse Q2 2026
What accounts for the gap
48%
of the difference between leaders who report value from AI and those who don't is accounted for by organisational readiness
McKinsey, Three Horizons 2026
What we measure
The reason for the change is clear, and everyone can explain it and see where they fit.
People ↔ the direction
Enough trust to get through the change together, and the safety to say out loud what isn't working.
People ↔ each other
Knowing where AI output needs to be questioned and overridden, and having the confidence to do it.
People ↔ AI
AI changes how teams work, so the work itself changes with it, rather than AI being added on top.
People ↔ the work
The diagnostic is designed to show the gap between how leaders see the change and how teams live it.
Sets the direction
Translate it
Live it
Anonymous by design: no group smaller than five is ever reported. About seven minutes to answer.
What adoption and value numbers don't show
Adoption and value tell you an AI transformation has started. Neither tells you whether it will hold.
Your AI programme · this quarter
Are your employees using AI? Who, how often, for what.
Usage dashboards and licence counts
Is it paying off? Productivity, savings, return.
Business cases tracked against the numbers
Are the relationships that decide whether the change holds working?
Measured by Ambit Index
How it works
Everyone answers, async and anonymous. Role and team are captured, because the gaps between levels are part of the diagnosis. You see exactly where the human system needs support.
The baseline sets the priorities. We tailor the work across the organisation, so it lands where it's needed most.
Everyone answers again. You see what moved, where, and what to work on next.
If your organisation is inside an AI change and the numbers you have don't tell you whether it's landing, that's the conversation we want.