University AI Policy: What Every School Needs

No AI policy is an AI policy. It just means you let everyone make it up as they go. And right now, that is exactly what most universities are doing.

The Gap Is Not Small

The numbers from the IREX and Development Gateway report are hard to ignore.

• 95% of students and educators already use AI tools (Coursera, 2026).
• Only 26% of institutions have a formal AI policy governing that use.
• Only 34% have a clear AI strategy tied to academic or operational priorities.
• Only 19% have actually built AI into how their institution operates day to day.
• Only 22% are measuring whether any of it is working.
• Only 37% report ongoing AI training for their staff.

That is a lot of adoption with almost no governance behind it. The technology is moving. The institutions are not.

What Happens Without a Policy

Here is what the policy vacuum looks like in practice.

One professor says AI is fine. The next one bans it outright. One office is experimenting with AI to run workflows. Another treats it like a form of academic dishonesty. Students get a different version of the rules depending on who they happen to be working with that week.

Nobody coordinated. Nobody decided. It just happened.

The student experience becomes inconsistent in a way that is hard to fix after the fact. And the damage is not just to their experience on campus. It follows them out the door. They graduate into a job market where employers assume AI fluency from day one. If their school blocked it, ignored it, or left it undefined, those students are starting behind.

The institutions that do not lead this will watch their students pay the price.

This Is a Governance Problem

The question is not whether students should use AI. That ship has sailed. The question is who decides how.

Right now, without a policy, the answer is: whoever happens to be in the room. That is not governance. That is abdication.

Not having an AI policy in 2026 is like not having an internet policy in 1999. The technology was already everywhere. Institutions that ignored it did not stop it. They just made sure their students navigated it alone, without support, and without any shared understanding of what was acceptable.

We know how that story ended. The institutions that embraced the internet and built real digital infrastructure pulled ahead. The ones that treated it as a threat or left it ungoverned fell behind. The same dynamic is playing out right now with AI.

What a Basic Policy Needs

This does not need to be a hundred-page document. A basic policy can be written in days. It needs to cover four things.

• 1. Define what AI is. Which tools are in scope? Generative AI, AI writing tools, AI embedded in software the school already uses? Clarity here prevents the endless argument about whether a specific tool counts.
• 2. Define when and how students and faculty can use it. Not just what is allowed or banned. When is it appropriate, and for what purposes? A blanket ban is unenforceable. A thoughtful use policy is something people can actually follow.
• 3. Decide where the school will invest in tools and training. A policy without resources is just a statement. Which AI tools will the institution provide? What training will faculty and staff receive? The report found only 27% of schools have dedicated AI budgets. That number needs to move.
• 4. Update it quarterly. A policy from 2024 is already behind the technology. Whatever you write today will need revision in three months. Build the review cadence into the policy from day one.

Policies Need to Evolve

Having a policy is better than having nothing. But a static policy is almost as bad as no policy.

Phil Hill at On EdTech noted that SUNY recently published an AI policy that is already governing yesterday's AI. The policy addresses ChatGPT-era concerns while the field has moved to agentic AI systems, workflow automation, and AI embedded in every major software platform. A policy that does not keep up with the technology creates a false sense of governance. The institution thinks the problem is solved. Students and faculty are navigating a version of reality the policy does not describe.

Quarterly reviews are not optional. They are the only way a policy stays useful.

The Cost of Waiting

Every semester without a policy is another cohort of students graduating without a consistent foundation in how to use AI at work.

Employers already expect new hires to use AI tools to complete real tasks. That expectation is not a future trend. It is the current reality in most industries. Students who spent four years under inconsistent or restrictive AI rules will feel that gap the moment they start their first job.

The institutions that get this right now will produce graduates who hit the ground running. The ones that wait will produce graduates who have to catch up on their own time, at their own expense, after already spending four years and significant money on a degree.

If you are not shaping how AI shows up on your campus, you are still making a choice. The question is whether that choice is intentional.

At Prentus, we work with higher education institutions to build AI-powered career infrastructure that delivers real student outcomes. If you are thinking about how AI fits into your career services model, we would welcome the conversation.