For organisations
Workforce AI readiness, evidenced rather than assumed.
The same discipline FutureMeasure applies to graduate readiness extends to the enterprise: understanding what a workforce can genuinely do with artificial intelligence, and building from that evidence rather than from confidence surveys.
- Planned service line
- University partnerships prioritised
- Evidence-led
The enterprise problem
Adoption has outpaced evidence.
Most organisations can report how many people have access to AI tools, how often those tools are used and how employees feel about them. Very few can say where consequential judgement is reliably sound, or where it quietly is not.
That distinction matters most in the functions where AI output feeds a decision someone will be accountable for: analysis, advice, compliance, clinical or financial judgement, and anything that reaches a customer.
A capability benchmark gives leadership something adoption metrics cannot — a defensible position on readiness, and a way to show that investment changed it.
Market evidence
The market is already paying for applied AI capability.
Uptake is broad and the premium is measurable. What remains unmeasured is where that capability is sound and where it only appears to be.
Across a sample of nearly one billion job postings. Published findings, not our results.
The wage premium for AI skills rose from 25% in 2024 to 56% in 2025. Source: PwC, 2025 Global AI Jobs Barometer.
Premium for roles requiring AI skills, versus roles without
More than 2× in one year
- 75%
of knowledge workers use AI at work
Microsoft · 2024 - 78%
of AI users bring their own tools to work
Microsoft · 2024 - 4×
faster productivity growth in AI-exposed sectors
PwC · 2025
Intended service line
Four components, drawn from the same research base.
Workforce readiness assessment
A structured picture of how well a workforce applies, verifies and governs AI in the work it actually does.
Capability gap mapping
Where capability is genuinely present, where it is assumed, and which functions carry the greatest exposure.
Development programme design
Learning and development priorities derived from evidence, rather than from a procurement catalogue.
Progress measurement
Repeated measurement so that improvement can be demonstrated to a board or a regulator, not just asserted.
These services are planned and not yet operating. Nothing on this page should be read as an offer of a current commercial service.
Sequence
Universities first. Deliberately.
The inaugural FutureMeasure cycle is focused on graduate AI readiness with universities. The enterprise proposition depends on the same instrument being validated in an educational setting first — we are not willing to run them in parallel and call both rigorous.
Organisations who would like to be informed when the workforce benchmark opens can register interest now. Early conversations will help shape what is measured.
Organisation enquiries
Register interest in workforce readiness benchmarking.
Tell us about your organisation and the capability question you are trying to answer. We will be candid about timing.