Buyer problem
The buyer needs credible evidence.
Leaders need to know whether employees can use AI safely, critically, and effectively in role-specific work.
Why traditional tools fail
Legacy tools see output, not thinking.
Completion rates, tool usage, and generic training surveys can overstate readiness.
How QLM solves it
QLM captures the process.
QLM uses scenario-based assessment, role-specific tasks, and living skills evidence to measure AI fluency.
Evidence captured
The pilot produces reviewable signals.
Evidence includes prompt judgment, verification behavior, risk reasoning, workflow transfer, and role-specific decisions.
Pilot design
A focused pilot can run before a district or institutional rollout.
Start with one role family, define AI competency expectations, and compare scenario evidence against training completion data.
- Select one cohort and one measurable outcome.
- Run QLM for a short cycle with teacher or leader review.
- Review misconception, reasoning, and evidence patterns.
- Decide whether to expand the pilot.
FAQ
Questions this page answers.
Is usage a competency metric?
No. Usage can show adoption, but competency requires evidence of judgment and performance.
Can assessment be role-specific?
Yes. QLM scenarios should be mapped to the decisions and risks of each role.
Next step
Turn the category into a pilot.
Use this path when you want a pilot, research partnership, or product walkthrough.
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