For organisations. AI and transformation readiness.

The most useful findings came from a slice no one had asked for.

The leadership team commissioned a workforce-wide AI readiness diagnostic and expected a scorecard. It got one. It also got three findings the scorecard could not show. They appeared only once the data was sorted by who was speaking and how long they had been there.

107
structured AI interviews across the workforce
4
seniority groups, from senior management to individual experts
3
tenure cohorts, including new joiners under one year
8
dimensions of readiness, on a four-level maturity ladder
3
findings the scorecard missed

What the business faced

A globally active industrial business had visible AI deployments running ahead of the structure that would let them scale. The leadership team wanted a calibrated read on where the workforce actually stood, across every layer, not another round of pilots.

How the read was run

Adaptive AI interviews ran with 107 employees in the language each chose, across four seniority groups and three tenure cohorts. The 8-A AI Readiness Framework placed the organisation across eight dimensions on a four-level maturity ladder, from L1 Ad Hoc to L4 Leading.

The scorecard, and what it missed

The scorecard placed the organisation at L1 Ad Hoc on six of the eight dimensions, with two at L2 Developing. Useful on its own, but not the most useful part. The deeper findings appeared only when the 107 responses were sliced by tenure and by seniority. None were on the scorecard. All three were in the data, and each one changed what to do next. Turn senior self-awareness into visible behaviour. Build the data case with the operators who can see the gap. And put an AI on-ramp into onboarding, before the system narrows what new joiners arrive with.

The scorecard view

The same data, sliced by seniority and tenure

Senior leaders were the harshest critics of the AI signal they themselves were giving.

More than half of senior managers

Around a third of first-line managers

Self-awareness was already in place, ready to be turned into visible behaviour.

Data-foundation problems were visible to operators and invisible to executives.

No senior managers raised this

Around one in seven first-line managers did

The closer to the equipment, the more credible the architectural gap.

New hires were arriving into an organisation without an AI on-ramp.

The great majority of new joiners said no AI learning path existed

The cleanest outside view of the system was also the most underserved.

What the business did with it

The report did not stop at delivery. A workshop annex turned the diagnostic into a one-day session built around the top three priorities, each one paired to a specific finding and a measurable signal of progress. The deliverable carried into the action.

Employees do not believe speeches. They believe friction removal and expectations.

Respondent, AI readiness interviews.

Yes, this is our work

AI and transformation readiness. Calibrate what your workforce really believes about AI, with depth across every seniority and tenure layer, not just a scorecard.

And across our practice. For organisations: team-read diagnostics on strategy, growth, AI readiness, and culture, plus custom 360 feedback built around your leadership model.

No, we will point you to a partner (when you want):

Crunch sales figures to set next quarter's pricing.
Run a one to five poll on the cafeteria's Friday curry.
A/B test which shade of blue your buy now button should be.
Find your next chief financial officer.
Migrate your data warehouse to the cloud.

Bring us the question you carry

If we are the right help, we will tell you. If we are not, we will say so, and where we know someone better, we will point you to them.

The 8-A AI Readiness Framework is co-developed by 100Facets and the University of St. Gallen.