Walk into almost any public university’s enrollment office and you’ll find the same scene: a financial aid system that doesn’t talk to the student information system, a CRM that can’t pull data from the registrar, and an LMS that exists in its own sealed universe. Staff spend hours manually exporting spreadsheets, copy-pasting data between platforms, and reconciling records that should have been connected automatically years ago.
This is not a technology problem. The APIs exist. The integrations are buildable. The data is there.
This is a leadership problem — and it is about to become a very expensive one.
In my thirty years working inside public higher education — including directing admissions operations across 25 CUNY campuses — I watched the same dynamic play out repeatedly. On one side, IT departments that understood infrastructure but had no meaningful grasp of how enrollment, advising, financial aid, and student success actually function together. On the other, academic and enrollment leaders who could articulate the student experience fluently but couldn’t speak technology’s language well enough to demand the right solutions. In the middle: students falling through the cracks between systems that were never designed to find them.
The result is institutions spending millions on platforms — Salesforce, Banner, Slate, EAB Navigate, Brightspace — that operate as expensive silos rather than as an integrated ecosystem. But the cost goes deeper than software licenses.
Consider what actually happens across a typical university on any given week. The enrollment office pulls its own spreadsheet. Financial aid pulls theirs. The registrar pulls another. The advising team builds its own report. Each department is analyzing the same students through a different lens, on a different schedule, with data that was never designed to speak to anyone else’s. Nobody sees the full picture. Nobody knows how much time is being collectively wasted. Add it up across departments, across campuses, across a system like CUNY — and you are looking at millions of dollars in redundant labor annually, in institutions where budgets are already stretched to the breaking point.
This was always inefficient. In a world where artificial intelligence is now being asked to help institutions understand their students, it has become a structural liability.
Here is the problem few people are talking about: AI cannot reconcile data it doesn’t know is equivalent. If credit hours are labeled one thing in the advising database and something slightly different in the SIS, an AI model asked to analyze student progression will fail — not because the AI is inadequate, but because the data foundation it is working from was never integrated to begin with. Garbage in, garbage out has always been true. With AI, the consequences are faster and more consequential.
The fix is not primarily technical. It requires leadership that understands both worlds — what the data should do for students and what it actually takes to make systems communicate. And here is the uncomfortable truth: this problem is not unique to higher education. In the private sector too, API connections between systems often go unbuilt — not because the technology doesn’t exist, but because nobody in the room knew to ask for them. The gap between the people who understand the business problem and the people who can build the technical solution exists everywhere. Higher education just has less margin to absorb the consequences.
Until universities close that gap — hiring and empowering leaders who can speak both languages, demanding integration over the next shiny platform purchase, and building data infrastructure that serves the whole institution rather than each department’s individual spreadsheet — no amount of AI investment will deliver on its promise.
The tools are not the issue. The leadership is.
