Where is your team exposed to AI — and who should you train first?
List your roles, rate how much each one already uses AI, and get a per-role gap score, a training order, and a first exercise for each. The interesting number is not how automatable a job is — it is how automatable it is while the person doing it isn’t fluent yet.
01 · Who is on the team?
Tick the kinds of work that fill this role's week — the score derives from that mix:
Add a role above — or load — and the gap cards, training order, and first exercises appear here. Nothing is sent anywhere unless you later ask us to email the report; the whole rubric runs in this page.
How the scoring works
Every role is a mix of nine kinds of work. Each kind carries an automatability estimate — our editorial call, stated openly below, of how much of that work today's AI tools could credibly take on or accelerate. A role's score is the mix-weighted average. The gap is that score minus how much the role already uses AI. High automatability with low current use is exposure without fluency: the riskiest place for a person, and the highest-value place to spend training.
| Kind of work | Automatability |
|---|---|
| Structured data entry & processing | 85 |
| Routine writing & drafting | 75 |
| Research & information gathering | 70 |
| Analysis & reporting on data | 65 |
| Customer & colleague communication | 60 |
| Scheduling & coordination | 55 |
| Creative & strategic work | 30 |
| Judgment calls, negotiation & relationships | 15 |
| Physical & hands-on work | 5 |
Current use runs on a five-point scale, from not using it to daily + building. Training priority multiplies each role's gap by its headcount, so six people with a moderate gap outrank one person with a big one — that is usually the right call for where a first cohort should come from.
What a score means — and what it does not
Automatability is not a layoff forecast. A high score means AI can credibly do or speed up much of the task mix — which is leverage for a person who is fluent and erosion for one who is not. The gap number measures that distance. A team whose high-exposure roles are all fluent has nothing to fear from this tool; a team whose high-exposure roles are at zero does, a little.
Three honest caveats. The estimates are ours — reasonable people argue over every number on that table, and the point of the exercise is the conversation it starts, not the second decimal. The task mixes for preset roles are typical, not yours; a support role that is mostly escalations is nothing like the preset. And current use is your read, which people systematically over-report — if a group's answer is “occasional experiments”, verify before you plan around it.
We keep the judgment-heavy categories scored low on purpose. Negotiation, sensitive calls, real creative direction — those get harder and more valuable in an AI-fluent team, not redundant. That split, automation for the repetitive and humans for the judgment, is the whole thesis of this company, and this tool scores against it.
From scores to a fluent team
The first exercises on each card are chosen so anyone can start this week — no budget, no vendor. What they cannot do is change a whole team's habits: that takes a program, real workflows as the curriculum, and measurement before and after. That is our AI upskilling program: cohorts that each ship a real automation, playbooks they keep, and numbers on what changed — not a lecture about the future.
Bring your gap cards to the first call and the survey step is already half done. Or start with a conversation— the checker is free either way, and nothing you typed into it leaves your browser unless you ask us to email the report.
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What we ship for clients, what the tools can honestly do this month, and one thing worth trying in your own team — written by us, no hype, unsubscribe anytime.