Over the past year at Tailwind, we have read and classified more than 1,500 real AI policies from colleges and universities. Community colleges, regional publics, big research universities, small private schools. I went in expecting to find a lot of thoughtful institutional governance. What I mostly found was something much narrower: a cheating rule for students, bolted onto a syllabus. 💡
Most campus “AI policies” in 2026 are not really AI policies. They are academic integrity rules wearing an AI costume.
What most campus AI policy actually is today
I do not want to hand-wave this, so here is what the data actually says. Of the U.S. policies we have validated, about 7 in 10 are framed as academic integrity documents. Roughly 6 in 10 are written for a single audience: students. And when we score a policy for maturity on an 8 point scale (who owns it, whether it covers staff and operations, data rules, training, human oversight, and how current it is), the median score is a 2 out of 8. Nearly half barely clear the first point or two.
- 71% are framed as academic integrity, not institutional governance.
- ~60% are aimed only at students, not staff, faculty, or operations.
- Median maturity is 2 out of 8. Almost half score a 0 or a 1.
- Only 17% mention staff training. Only 28% require human oversight.
I want to be clear: I am not knocking the people who wrote these. Most were written fast, in 2023 or 2024, by a committee that needed to tell students something before midterms. That was the right instinct at the time. The problem is not that these policies are bad. It is that the world moved, and most of the documents did not.
Why a student cheating rule is no longer enough
AI walked out of the student essay and straight into the back office. Staff are now using it to draft emails, build spreadsheets, answer student questions, summarize meetings, and screen applications. A policy that only tells students “disclose AI on your assignment” governs none of that.
The real risk in 2026 is not a student submitting an AI essay. It is a well-meaning employee pasting FERPA-protected records into a public chatbot, or an unreviewed AI tool quietly shaping a financial aid decision. Those are institutional risks, and a student-facing integrity rule does not touch them.
The question is no longer “are students using AI?” It is “is everyone on campus using AI, and does anyone know how?”
What a workable policy actually looks like
Here is the structure we keep coming back to. The good news is that a workable 2026 policy does not have to be long or full of legalese. It just has to do these seven things:
- Owned at the top. Adopted by the board or cabinet, not buried in a department FAQ. Only about a third of the policies we have seen have real ownership behind them.
- Built for the whole institution. It covers faculty, staff, administrators, student workers, and vendors, not just students. Today only around 30% do.
- Governed and enabled, not banned. The healthiest stance is conditional: here is how to use AI well, with guardrails, rather than a blanket “no.” Blanket bans are both rare and basically unenforceable.
- Clear on data. It names what must never go into an open AI tool: FERPA-protected student work, personnel records, non-public financial data.
- Backed by training. People cannot follow a policy they do not understand. Only 17% of policies require any training, which makes this the single biggest gap in the sector.
- Insistent on human oversight. AI assists, a human decides and signs off. High-stakes calls (admissions, grading, discipline, aid) stay with people.
- Kept current. AI changes month to month. The policy needs a named owner and a review date, or it is stale the day it ships.
The one I keep pointing people to: Delta College
In June 2026, the Delta College Board of Trustees in Michigan adopted Board Policy 8.020. When we ran it through our scoring, it did something almost nothing else in the database does: it hit all seven of those points. A perfect 8 out of 8, against a national median of 2. 🙌
What they got right:
- The board itself adopted it (Board Action 5701, June 9, 2026). That is real ownership, not a committee memo.
- It applies to everyone: faculty, staff, administrators, student employees, contractors, vendors, consultants, and partners.
- It is enabling, not fearful. It sets out to encourage innovation while preserving human judgment and equity.
- It draws a hard line on data: no FERPA-protected work, personnel records, or financial data in open AI systems.
- It requires every employee to complete AI training before using AI in their official duties.
- It keeps humans in charge: “AI may assist but may not replace human judgment,” and all AI-generated content must be reviewed, verified, and edited by the user.
- It vets tools before they are used, through an IT governance committee, including legal, privacy, security, and accessibility review.
What I love about it is that it is not academic. It reads like it was written by people who actually thought about the advisor, the receptionist, and the financial aid officer, not just the English 101 student. That is the entire shift captured in one document. Hats off to the Delta College team. ❤️
Where to start (you do not need a perfect policy)
If your current policy is a single paragraph in a syllabus, that is okay. You do not have to leap straight to an 8 out of 8. Here is the order I would tackle it in:
- Widen the audience. Take your existing student rule and ask one question: what does this say to our staff? If the answer is “nothing,” that is your first gap.
- Name your data rules. Even one clear sentence about what never goes into a public AI tool puts you ahead of most institutions.
- Give it an owner. Assign the policy to a person or committee with a review date. Staying current is a choice, not an accident.
- Add training before tools. A policy is only as strong as the people who understand it.
- Borrow shamelessly. Delta College’s policy is public, and so are hundreds of others. You can browse them for free in our AI Policy Database. There is no reason to start from a blank page.
None of this is about slowing AI down or wrapping your campus in red tape. It is the opposite. A clear, fair, well-owned policy is what lets your people use these tools with confidence, and that confidence is what frees them up to do the thing we all signed up for: help students. 🫶
If you are staring at a one-paragraph AI rule and wondering how to grow it into something real, that is exactly the kind of conversation we love to have. No pressure, no jargon, just a practical next step for where your campus is today. 🤝