For universities
Clear insight into what your graduates can actually do with AI.
Establish where capability genuinely sits across your cohort, defend that position with evidence, and turn it into curriculum, employability and capability decisions.
- Founding partnerships open
- Assessment in development
- Ethics-led design
Sector evidence
Use is near universal. Evidence of capability is not.
Students have adopted the tools faster than institutions have measured what they can do with them. Employers are still screening for the underlying capabilities.
Reported use in studies — 1,041 UK full-time undergraduates. Published findings, not our results.
| Year | Share of students (%) |
|---|---|
| 2024 | 66 |
| 2025 | 92 |
Select a point for the reported figure
Δ +26 points in one year
| Attribute | Share of employers (%) |
|---|---|
| Problem-solving | 88.7 |
| Teamwork | 78.9 |
| Written communication | 72.7 |
| Verbal communication | 67.5 |
| Analytical / quantitative | 66 |
Share of employers seeking evidence on a graduate résumé
What you gain
Six things participation should give you.
Deliberately specific. We would rather promise a small number of things we can defend than a dashboard of things we cannot.
A readiness profile you can present
Capability evidence across the proposed domains, ready for council, quality review or accreditation discussion.
Where the gaps are, precisely
What is strong, what is uneven and what is absent — by domain and by discipline, not one blended number.
Implications for teaching
Interpretation notes written for academic decision-makers, mapping findings to curriculum and assessment design.
A structured debrief
A working session with faculty and learning and teaching leadership to agree what happens next.
Influence over the method
Review of the framework and of findings before anything is published, including the right to disagree on record.
A baseline you can re-measure
A cohort position to return to, so progress can be demonstrated rather than asserted.
Comparative and sector-level insight depends on participating datasets and will only be offered where the evidence supports it.
How it works
Four stages, from first conversation to usable evidence.
Scoping conversation
A structured discussion with academic leadership to establish the question you need answered, the cohort of interest and any ethics constraints.
Instrument review
Proposed assessment content is shared for faculty review and ethics approval before any student is involved.
Piloting
A cohort completes the assessment under agreed conditions, with results used to examine both student capability and the instrument itself.
Interpretation and reporting
Findings are reported at domain level, discussed with your team, and translated into implications for teaching.
The journey above describes the intended model. Stages, instruments and reporting will be finalised with founding partners, each subject to institutional ethics approval.
Why founding partners
Participate in the design, not just the results.
Founding partners join while the framework is still open to argument — which is where the useful influence is. Your faculty can challenge what counts as readiness and refuse what would be reductive in your disciplines.
We are not promising scale, accreditation or a published ranking. What we can promise is a rigorous attempt, made openly, with your institution inside the process.
Working in an organisation rather than a university? Read the workforce brief.
Founding partnership
Discuss a university partnership.
A first conversation is exploratory. We will explain where the work stands, what participation would involve, and what we do not yet know.