Policy & governance
“Students are already using AI — and we have no policy.”
An AUP update can't govern AI. You need policy that covers automated decisions, vendor data practices, and staff use — not just ChatGPT in the classroom.
The clear-eyed read
What's actually going on
You are not behind because you are careless; you are behind because the tools moved faster than any governance cycle can. 81% of teachers report their district has no formal AI policy — while a large majority of students already use generative AI. The gap between practice and policy is now the norm, not the exception.
The instinct is to bolt a paragraph onto the acceptable-use policy. That instinct is wrong, because AI in a district is not one thing. It is a classroom tool, yes — but it is also an automated decision-maker in HR screening and scheduling, a data pipeline inside vendor products, and a silent feature update in software you bought three years ago. If your policy only addresses students and chatbots, it is governing a fraction of your actual AI use.
Michigan's MDE guidance (May 2026) is a meaningful first step, aligned to the MICIP continuous-improvement cycle. But it does not provide board-adoptable policy language, an enforceable prohibited-uses list, a risk-tiering rubric, or an appeal process. Treat state guidance as a floor, not a ceiling — and build the rest deliberately. Vague guidance is not policy.
First moves
30 / 90 / 365 days
Sequenced, not simultaneous. The 30-day moves cost little and buy you room; the year is where the change becomes structure.
First 30 days
- Stand up a small AI workgroup with a named owner — not a committee of everyone.
- Inventory actual AI use: tools staff use, AI features inside existing vendor products, and what students report using.
- Adopt an interim staff rule set (approved tools, data rules) so guidance exists while policy is drafted.
By 90 days
- Draft policy against the twelve components of a complete district AI policy — from purpose and definitions through procurement and review.
- Run the draft past legal counsel and your board policy committee; borrow tested language from strong model policies rather than starting blank.
- Set the risk-tiering rubric: which uses are low-risk, which need review, which are prohibited.
Within the year
- Board adoption, public communication in plain language, and a standing review cycle — policy that never gets revisited is policy that stops working.
- Fold AI review into procurement so every new tool and every vendor feature change passes through the same gate.
Carry the work
The tools that carry this
AI Policy Playbook for K-12 Districts
The 12-component framework, model-policy profiles, draft board language, and the 30/90/365 sequence.
Policy Gap Checker
Check your current policy against the twelve components; get a ranked gap list. (Coming soon.)
Policy & Guidance
The full policy section of this site, including the Michigan picture.
