Higher education is moving past its initial uncertainty about artificial intelligence and is now racing to keep pace. According to a recent survey from EDUCAUSE, two-thirds of institutions are actively piloting AI tools. But as with any new technology, colleges and universities risk moving too quickly, adding new tools to existing processes without considering whether those processes are still serving students. When that happens, institutions reduce technology to a surface-level convenience rather than a catalyst for meaningful change.
AI has immense potential to help simplify arcane workflows, generate data to improve outcomes, and provide a more seamless experience for both students and administrators. Those benefits can only emerge, however, if college leaders redesign their processes alongside the implementation of technology. To realize the full value of AI and other emerging tools, institutions need to reimagine their systems, not just digitize them.
The sector has faced similar inflection points before. When online learning emerged, institutions that attempted to simply recreate the classroom experience on a computer screen quickly discovered that the medium demanded something fundamentally different. Lifting a process from one context and placing it into another without reimagining it produced predictably poor results. Institutions learned they needed to redesign courses from the ground up. That lesson took time to take hold, but today’s online learning looks nothing like those early attempts.
The pattern tends to repeat itself: A new technology arrives, institutions feel pressure to adopt it, and they choose the path of least resistance by layering it onto existing processes. While this can create the appearance of greater efficiency, it can just as easily increase student frustration and fall short of delivering the meaningful insights the technology promises.
Today’s students are generally not left wanting for technology. They are surrounded by a wide array of tools, platforms, and resources designed to support them. But when so many systems are layered on top of one another—without enough attention paid to the processes they’re meant to improve—that abundance can start to feel overwhelming.
A more efficient bad system is still a bad system. It just moves more quickly. Instead, institutions should ask harder questions, both about how best to deploy a new tool and whether any underlying approaches still make sense.
As the founder of a student success platform that partners with dozens of colleges and universities around the globe, I have seen firsthand how institutions can struggle when they apply new technology to processes that are already not working. Dan Sullivan and Benjamin Hardy describe this distinction in their book 10x Is Easier Than 2x. The “2x” approach focuses on doing the same work only faster, while the “10x” approach requires eliminating low-value work and concentrating on the activities that create disproportionate impact.
Too often, colleges approach AI as a 2x tool, when the technology’s full power can only be unlocked when used in a 10x fashion, with institutions rethinking which processes actually help students. In other words, the question institutions should ask is not whether they can use AI to do more of the status quo, but how they can use AI to do less of the wrong things altogether.
Consider the college senior who needs one final course to graduate but discovers that the only remaining section is completely full. She has no clear path forward but to extend her time to a degree. An AI chatbot delivering the bad news does not solve the problem. But a better-designed, more connected system that uses AI to flag bottlenecks much earlier can help prevent these challenges before they disrupt a student’s path to graduation.
Some institutions are starting to take a different approach, using technology implementation as an opportunity to fundamentally rethink how they operate.
At Pittsburgh’s Duquesne University, for example, the degree audit system had become so unreliable that the registrar’s office felt compelled to add disclaimers to its own reports. Untrusting of the information the system provided, students worked around it by relying on printouts and personal spreadsheets. When the university introduced a new degree-planning platform, the Duquesne staff did more than just swap out the technology. They cleaned up years of inconsistent data and consolidated four disconnected systems into one. Graduation clearance, which once took hours of manual effort, now takes about 30 minutes.
Students at the University of Wisconsin–Stout once faced a similar challenge. For years, the university relied on a network of more than 50 program directors to independently advise students on their schedules. The approach was inconsistent and time-consuming.
When the university moved to a new advising platform, it redesigned the workflow from the ground up, creating a more coordinated process, rather than digitizing the original, more fragmented approach. Today, approvals for substitutions and exceptions happen 10 times as quickly, often in a matter of seconds.
Technology delivers the greatest value when institutions use it to rethink how they support students, not only to speed up existing tasks. Institutions should bring that same discipline to how it uses artificial intelligence.
AI is a powerful tool, but it is not a miracle cure on its own. No tool is. Institutions that get the most from new technologies use them to reimagine how they serve their students.
