Your institution hasn't stood still since January, and your systems haven't either.
You've onboarded new faculty and staff, brought on adjuncts and student workers, adopted new tools and made fast calls to keep things moving. Faculty and staff have almost certainly started experimenting with AI, too — often before anyone set a policy for it.
What's hard to keep track of is the trail those decisions leave behind: who still has access to systems they no longer need, where student and research data ended up, and who's responsible for what.
By summer, most institutions are running on assumptions about how their systems work. With fall enrollment approaching, here are four things to examine before those assumptions become expensive.
1. Access was expanded. Was it ever revisited?
New hires needed to get on systems quickly. Faculty moved into new roles and picked up permissions along the way. Adjuncts, student workers and temporary staff were granted access to keep a course or project moving.
But access almost never gets revisited after it's needed, which means the picture on most campuses looks like this:
- People have more privileges than their current role requires
- Departed faculty, graduated students and former student workers likely still carry active permissions
- No one has a clean view of who can reach student records, financial aid data or research files
It's time to ask: do the right people have the correct access today?
Do you know who can see what inside your institution right now? If that answer takes longer than a few seconds, pay attention — FERPA assumes you do.
2. Your tools solved problems while creating new ones
Admissions needed a better way to manage applicants, so a platform was added. A department adopted its own scheduling tool. A research group signed up for cloud storage. Marketing brought on software to run campaigns faster. And somewhere along the way, faculty and staff started pasting work into AI assistants to move faster.
Every one of those was a reasonable decision. Collectively, they created something messier.
Data now lives in more places, integrations were set up quickly and may not be working as intended, and visibility across systems has fragmented. When AI tools enter the mix without guidance, sensitive student or research information can end up in places no one is tracking.
When systems coexist without anyone owning the full picture, the risk doesn't announce itself. It shows up later in slower decisions, inconsistent reporting and gaps that belong to nobody.
Do your systems work together, or is your staff quietly working around them? By the time that question becomes urgent, it's been a problem for a while.
3. Your backup and recovery confidence is probably assumed
Most institutions have backups in place and operate under a false sense of security. Recovery is rarely tested, the timeline to restore the SIS or LMS is unclear, and ownership of the process often isn't defined.
When something goes wrong — ransomware, a server failure or an accidental deletion right before grades are due — the conversation starts with "wait, who handles this?"
Having backups is not the same as being able to recover. The difference only becomes clear at the worst possible time, like the first week of the term.
If a core system went down tomorrow, would you know exactly what happens next? Or would you be figuring it out on the spot?
4. Responsibility has blurred as your campus has grown
Remember when who owned what was clear?
Central IT handled certain systems, departments handled others, vendors handled the rest, and responsibilities were roughly defined even if nobody had documented them.
Then systems expanded, new vendors came in, departmental IT shifted and somewhere in all that growth, ownership got blurry.
Now when something breaks and it crosses departments or providers, who takes the lead often gets answered in real time. Issues bounce between central IT and departments, small problems sit unresolved, and nobody's sure whose job it is to fix them.
When something alarming happens in your systems, do you know who's responsible for resolving it? Or do you figure it out in the moment?
Most risk doesn't come from what's broken
It comes from what's changed without being revisited.
Institutions that stay ahead of this aren't doing anything complicated. They have a clear view of who has access to what, they know their backups work, and they know who owns what when something goes wrong. They also know how faculty and staff are using AI — and have made sure people are trained to use it safely.
That clarity lets a campus move fast without things falling through the cracks.
That's what we're here to help you achieve. And because AI readiness has quickly become part of operating securely, we built Project NoéMI™ — credentialed with George Mason University — to help your faculty and staff get there, starting with a free first step.
Sign up for the free AI Acceleration Platform: https://forms.newpush.com/join-noemi-trainer. Want a straight answer on where your campus systems stand today and what needs attention before fall? Book a 15-minute discovery call.
