How a campus measures AI readiness in 20 minutes

This short explainer walks through the single question every placement team now faces — ‘how AI-ready is this graduating class, really?’ — and shows how an institution can answer it with a number rather than a hope. It follows one cohort from a cold baseline to a measured, provable lift.

What you'll see

• Baseline — how a whole cohort is assessed on a common readiness measure in a single sitting.
• Diagnose — reading the results to find where the gaps actually are, by skill and by group, rather than where they are assumed to be.
• Close — directing guidance and skilling to exactly those gaps instead of spraying generic content at everyone.
• Prove — re-measuring to show the lift, and issuing credentials graduates can carry to employers.

Key points

• A readiness baseline turns a vague mandate into a managed number you can move.
• Targeting skilling at measured gaps is dramatically more efficient than uniform programs.
• The same measure used to diagnose is the one that proves the lift — and that employers trust.

The point of the walkthrough is not the tool but the shift in posture: from talking about AI-readiness as an aspiration to managing it as a measurable outcome, cohort by cohort.

Watch

The video is arriving in 2026. Subscribe to The AI Growth Brief and we will send it the moment it is published.