AI fluency, measured
Your workforce.
AI native.
Enable.ai measures how well your people work with AI. Role by role, on one calibrated scale.
Put your AI budget behind the teams that can use it, and show leadership it's working.
See how candidates actually work with AI, on a real task from the role. One scale for all, so your shortlist runs on evidence, not charm.
Where AI fluency sits today, team by team and role by role. Measured, not surveyed.
We name each team's gap. Training closes it inside the work, not in a classroom.
Rollouts stall on process, not people. A fluency baseline shows what to fix first, and gives your AI strategy a number to hit.
Building the AI fluency standard with
The upside you've already paid for
Six questions.Six different desks.One answer.
Talent Acquisition LeadTechnology company
- Why you can't answer it today
- Every CV, take-home and interview answer now has AI in it. The output no longer tells anyone apart, so interviewers fall back on who talks well.
- What to do instead
- Add a twenty-minute AI fluency assessment where your screen sits today. Candidates work a real problem from the role, AI tools open. You get four signals against the role's band, straight into your ATS.
- What changes
- Interviewers spend their hours on people worth their hours. And when someone asks "why this candidate?", you have the session to show them.
HR DirectorFinancial services
- Why you can't answer it today
- Adoption dashboards tell you who logged in. No board has ever accepted a licence chart as proof of fluency.
- What to do instead
- Run the assessment across functions. Get a fluency map of the organisation you actually have: by team, role and level, against your sector.
- What changes
- You find the teams that are AI native and the ones coasting. And you stop funding training for a gap that's somewhere else.
CFOIndustrial group
- Why you can't answer it today
- You know the seat count and the invoice. The return depends on how well each person uses AI, and none of your dashboards show it.
- What to do instead
- Put the fluency map next to the seat allocation. They rarely match, and the gap is usually obvious at a glance.
- What changes
- Seats go to the people who turn them into results. Next time the AI line is questioned, you answer with a measurement, not a hunch.
CEOProfessional services
- Why you can't answer it today
- Every AI strategy assumes a workforce fluent enough to deliver it. Almost nobody checks, and by the time anyone asks, the timeline is public.
- What to do instead
- Take a fluency baseline in every function, then measure again each quarter. You see readiness by team, each team's weakest signal, and the direction of travel.
- What changes
- You roll out where fluency already exists and invest where it doesn't. Your AI strategy gets a success metric: fluency by team, every quarter.
Engineering DirectorSoftware company
- Why you can't answer it today
- Performance reviews read output. With AI in the loop, output says less and less about the person, and talent decisions quietly get worse.
- What to do instead
- Fluency, signal by signal, shows what each person is strong at and exactly what they're missing, with the evidence. Measure again to see if development worked.
- What changes
- Development budget aimed at a named gap, not a generic AI course. Promotion cases that hold up when someone challenges them.
Strategy DirectorListed group
- Why you can't answer it today
- There's been no shared scale. Every organisation marks its own homework, with a rubric it wrote itself, and calls the result a benchmark.
- What to do instead
- Every assessment feeds one AI fluency index, calibrated across industries, countries, functions and levels. You're placed against companies that are actually comparable: your sector, your roles, your markets.
- What changes
- You tell the board where your AI maturity stands, not how you feel about it. And next time, you show the direction of travel.
The AI Interviewer
The AI fluency assessment.
A live, twenty-minute session with our AI interviewer, built around the role.
Four steps, twenty minutes.
One live session. One calibrated score.
You name the role and level. We tune the session to the fluency that role needs.
A real, open problem from the role, AI tools open. The interviewer digs in when an answer goes thin.
Recognition, direction, taste and refinement. Scored the moment the session ends, against the role's band.
Plugs into Greenhouse, Workday, Ashby and Lever as a stage in the process you already run.
What AI fluency is made of.
Skills tests and adoption dashboards try to guess it. We measure it, in four signals that each stand on their own.
Seeing what's really being asked before writing a prompt. Most weak AI work fails right here, quietly.
Knowing what good looks like, and saying it clearly enough for a machine to aim at.
Spotting a plausible answer that's wrong. The signal that sets the best apart.
Pushing past the first output until the work is actually finished.
Why today's assessments miss AI fluency
Everything you run today was designed for someone working alone.
How do you assess people today?
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Why choose Enable.ai?
Understand your talent gaps
Know your team's fluency.
Know who to hire next.
Most organisations have a gap on both sides. Start at either end. You'll end up in the same place.
A fluency map of the organisation you actually have. Not the one on the org chart.
Candidates compared on how well they work with AI, not how well they interview.
An AI fluency index
AI maturity you can measure & compare.
Every assessment feeds one AI fluency index. It works like a credit score that helps calibrate you towards your industry standard.
Measure fluency
See where AI fluency sits today, role by role, against your sector.
Build fluency
Training inside the work, aimed at each team's weakest signal.
Track AI maturity
Success metrics for your AI strategy, measured every quarter.
Start with one role
Your AI strategy now has a roadmap.
One role, one cohort, a few weeks. Then you'll know: