Does your staff actually know how to use AI? Measure it before you mandate it.
Before your institution writes an AI policy or buys training, run the diagnostic: five minutes per staff member, a readiness picture per faculty, and a record that stands in any review.
Department AI Literacy Mosaic
Visualize employee performance, composite scores, and team averages across your entire organization.
Workforce AI Heatmap
400 Employees Audit Sample 路 Org Average: 62/100
1. Executive & Strategy
30 people 路 Avg 712. Commercial & Revenue
110 people 路 Avg 523. Engineering & Product
120 people 路 Avg 814. Marketing & Growth
60 people 路 Avg 675. Operations, HR & Legal
80 people 路 Avg 41A readiness picture per faculty
See which departments can already work with AI and which cannot - verified by a real task, not a survey.
Policy built on evidence
An AI policy written without knowing staff capability is a guess. The diagnostic gives the policy a baseline and every later review a comparison point.
Judging AI output is the core skill
The diagnostic measures whether staff can evaluate AI output rather than accept it - the skill under every academic integrity policy.
Five minutes per staff member
A short intake on role and tools, then one real, scored prompt task. No workshop to schedule, no teaching day lost.
The results come back as a heatmap per faculty, a readiness assessment per team, and a scorecard per person.
"We publish only real numbers. Diagnostic pilots are running now - ask in your demo for anonymized sample heatmaps and scorecards."
Mandates without measurement do not stick
Institutions that mandate AI training without a baseline get completion statistics and little else.
Measure first: the diagnostic shows who needs what, so training lands where the gaps are - and staff who already have the skill are not sat through a course they could teach.
Frequently asked questions
Ready to see where your staff stands?
A demo shows the diagnostic on your institution - faculty heatmap, team readiness, per-person records.