A good AI acceptable use policy (AUP) is what keeps employees productive with AI tools without exposing the organization to data leaks, copyright problems, or regulatory penalties. But many policies are written quickly and miss whole categories of risk. The AI Acceptable Use Policy Scorer reads your existing policy and tells you which best-practice topics it covers and which are absent.
How it works
The tool checks your pasted policy text against ten weighted benchmark areas drawn from common AI governance frameworks: data handling rules, defined permitted uses, explicitly prohibited uses, disclosure obligations, mandatory human review of outputs, intellectual property treatment, security and shadow-tooling controls, vendor training opt-out requirements, enforcement consequences, and policy scope and ownership.
Each area is detected through keyword and phrase patterns. The higher-risk areas — data handling, permitted and prohibited uses, and human review — carry more weight, so a policy that nails the fundamentals scores well even if it skips a minor section. The result is a 0–100 coverage score and a checklist showing exactly which sections are present.
Tips and notes
Use the score as a drafting checklist rather than a grade. The most frequently missing sections are vendor training opt-out (whether providers may train on your data), disclosure rules (when AI involvement must be flagged), and concrete enforcement consequences. Adding clear wording for those three closes most gaps.
Because the tool matches topics rather than judging quality, a confident-sounding policy can still score poorly if it never names a topic — and a checked item still needs review by someone who knows your obligations. All analysis happens in your browser, so you can safely score internal policies that have not been published.