Recognise before diagnosing
Surface useful foundations before explaining what further evidence is needed.
Why DEEP
AI literacy should improve practice, not manufacture confidence.
DEEP is built around a simple principle: schools should be able to see what their evidence supports, act proportionately and demonstrate what changed.
The problem
A score without evidence is not assurance.
School AI practice is rarely captured in one policy. It appears across curriculum, assessment, safeguarding, professional learning, leadership decisions and classroom artefacts.
A useful audit must recognise those foundations while remaining honest about what they do not yet establish. It should help a school improve the evidence and the practice, not reward polished documentation or infer activity that was never supplied.
That is why DEEP connects the audit to action, creation, retention and follow-up review rather than ending with a report.
Design principles
Keep uncertainty visible
A withheld judgement is safer and more useful than a confident guess.
Match the response to the work
Strategic, departmental and classroom priorities require different outputs.
Preserve the baseline
Progress can be understood only when the original evidence position remains intact.
Keep people accountable
AI can support analysis and creation, but authorised people approve evidence, action and release decisions.
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