Below is one division's org chart. Scroll through how an AI Assessment turns it into an adoption plan — who to train, who to coach, who to champion.
His division on paper: twelve people, four teams — and nothing on the chart says who's ready for what.
One assessment colors the whole division: a capability level and a persona for every person, plus tags where action pays off first.
The goal: everyone using a chat assistant in their own work for a 10–20% productivity boost — and discovering their own use cases along the way.
Andrew, Sean and Brian all practice at Level 3. But leading a division through AI is a different ladder — Andrew is an L5 AI leader whose own usage is L3.
Leading in AI doesn't mean knowing its nuances. It means understanding how it works — well enough to point a team with it. We develop both tracks.
Marcus and Rachel got here on their own. Give them the campus sandbox to push as far as they can, help them stay on top of AI, and a room where their ideas get heard — that's your champion bench.
Eric already builds. What he needs is time to stay on top of tech that shifts monthly — and a clear signal that the campus is behind him.
We measure the team, map the journey, and hand you the plan.
Book an AI Assessment ConsultThe point of measuring isn't the label — it's that each level implies a different kind of development. Here's what the spread you just scrolled through means in practice.
General AI education, delivered broadly: what the tools are, what they're good and bad at, and how to use them productively and safely in everyday work. Structured, cohort-style training pays off most here — and in this division, that's half the team.
Level 3s are pro-AI and productive — and capped out. They can't move forward without dedicated time and focused training for the biggest leap on the ladder: L3 to L4. For the leaders among them, add strategic thinking about AI — priorities, change, where to point the team — more coaching than curriculum.
The L3-to-L4 leap runs on creativity, curiosity, and self-directed learning — most L4s got there through side projects, on their own time, with their own tools. What they need from the institution is systems thinking: specific, targeted training that turns working prototypes into things a team can rely on.
Systems Builders combine programming and systems thinking — and most built that capability at home, because the institution doesn't yet provide the tools. What they need is time and support to stay up to date in a field that shifts monthly, and a mandate to bring what they learn back.
The division above is a synthetic sample — no real people, no real college. But every pattern in it comes straight from real assessment conversations. See the leadership dilemma that leads here →
Schedule a free 60-minute AI Assessment Consult. We'll learn about your team, the decisions you're facing, and where AI may fit, then help you determine whether an assessment makes sense.