How to write an AI use policy for your school or classroom

Most schools now have some form of AI policy - but the majority are either so general as to be unenforceable or so restrictive as to be unrealistic. 'AI tools may not be used without teacher permission' doesn't tell a student whether they can use a grammar checker. 'ChatGPT is banned' doesn't address the dozens of other AI tools now embedded in everyday software. Writing a policy that actually works requires more specificity than most schools have achieved so far.

Why most AI policies fall short

The core problem with blanket AI bans is that they treat all AI assistance as equivalent. Using a grammar checker to fix a comma is categorically different from generating an entire essay. Both technically involve AI; treating them identically misses the educational distinction. Students who can't see the logic behind a rule are also less likely to internalise its purpose.

Another common failure is policy written at institution level that doesn't translate to classroom practice. A school-wide document saying students must check with their teacher before using AI tools is fine in principle, but without per-assignment guidance, it creates uncertainty at the moment it most matters. The student is at home at ten o'clock at night, not sure whether using AI to help them understand a concept crosses the line.

The task-by-task approach

The most functional approach to AI policy in classrooms is per-assignment clarity rather than institution-wide rules alone. For each piece of assessed work, specify what kinds of AI assistance are and aren't acceptable. This takes more upfront effort but substantially reduces ambiguity - and it aligns the policy with the actual educational purpose of each task.

Consider three broad categories: tasks where no AI use is acceptable (the work must demonstrate the student's unaided ability), tasks where AI assistance is acceptable as a tool but the final writing must be original, and tasks where AI-generated content is explicitly permitted and the assessment focus lies elsewhere. Making these distinctions explicit, per task, removes much of the grey area.

Tools like Learnaway support this directly: you can specify the AI-use policy at the point of creating an assignment, so students see the expectation when they open the link. That specificity reduces the number of students who claim they didn't know the rules.

Language that students actually understand

Policy documents written in institutional language often fail because students don't read them, and when they do, the abstract framing doesn't map to the specific situations they're navigating. Policies that include concrete examples - 'using AI to generate your introduction is not permitted; using AI to check your spelling after you've written your draft is fine' - are more likely to inform behaviour than those that rely on students to interpret general principles.

Including worked examples of acceptable and unacceptable use is worth the additional space. Students benefit from understanding where the line is drawn, not just that a line exists. Teachers who have explained this interactively report considerably fewer borderline cases than those who've simply referenced the policy document.

Enforcement and fairness

A policy is only as good as its consistent application. Several things undermine consistency: informal enforcement decisions that aren't documented, different thresholds applied to different students, and formal processes triggered without adequate evidence. A useful policy connects clearly to your evidence standards.

What counts as evidence matters. A text-based AI score is a probabilistic signal with known bias problems against non-native English writers. A process log from a writing session - showing that an essay appeared as a single paste event in thirty seconds - is a statement of fact. Your policy should specify what level of evidence is required before formal action is taken, not just what the rule is.

What to include and what to leave out

A workable classroom AI policy needs: a clear statement of which types of AI assistance are acceptable per task, the reasoning behind the distinction, a statement about how submissions are collected and what data is captured, and the consequences of policy breach with proportionate severity.

What to leave out: exhaustive lists of banned tools (these date quickly as products change), vague commitments to 'monitoring' without specifying what that means, and penalty structures that treat all AI misuse as equivalent to deliberate cheating. A student who used AI to generate one paragraph and then rewrote it substantially is in a different category from one who submitted wholly generated text with no engagement. A proportionate policy should be able to reflect that distinction.