Most conversations about AI in higher education stay stuck at the level of "this is important." This one didn't. Brian McDowell, Head of Partnerships at Stellic, sat down with Jim Bouse, a longtime registrar leader and past president of AACRAO, along with Gates Bryant and Daniel Brennan from Tyton Partners, for a working conversation about what AI actually looks like inside enrollment, the registrar's office, advising, and leadership right now. The goal was practical: what has changed, what it means for your job, and what you can do next.
You can watch the full session below. If you want to bring a data-driven point of view to AI conversations on your own campus, Tyton Partners' research is a great place to start. And if you would like to see where your team stands, our three-minute AI fluency assessment gives you a report right away.
Tyton Partners has advised the education sector for more than fifteen years, and their working assumption has always been that technology outruns the sector's appetite to adopt it. AI broke that pattern. Drawing on their research, Gates and Daniel shared that north of 80% of both faculty and administrators now agree that AI has the potential to transform teaching and learning, and most say that transformation is already underway. What surprised the panel most was where the growth is coming from. Administrator adoption has climbed sharply, driven by real use cases rather than a vague sense that they should be paying attention.
Jim framed the tension well. The technical curve is climbing fast while campus processes, policy, and procurement move at their own speed. The work ahead is closing that gap without freezing the people who need to use these tools every day.
A recurring thread was that confidence in AI rises the more people actually use it, and that better models have made a real difference. Gates pointed to how much easier it has become for these systems to attribute their answers back to underlying data and to connect cleanly to institutional sources. That transparency is part of what moved skeptics off the sidelines.
Data quality is the multiplier underneath all of it. Institutions that grade their own data an A or a B are far more likely to believe AI can help them. The encouraging part, as Gates put it, is that improving data quality is not a once-and-done project you have to perfect before you start. Human judgment still matters enormously here. AI is not replacing the experienced person who knows what they are looking at, and Jim reinforced the point with a clear checklist for any campus: know where your data lives, who owns it, how it is protected, and what guardrails sit around the agents making decisions.
The heart of the session was a tour through the functions everyone on the call recognized. In enrollment, Jim talked about reducing friction for families making one of the largest financial decisions of their lives, using predictive insight and clear next-step guidance so students always know what to do next rather than waiting on hold. In the registrar's office, he made the case that registrars should be less the brake on AI and more the legal-style guidance that helps the institution move forward correctly, with someone from that office at the table for every contract review and data governance conversation.
When an attendee asked whether tools like Cowork might replace niche systems like CourseLeaf, Gates offered a sharp read. He doesn't expect a return to homegrown systems, but he does see a new operating model taking shape, where IT staff pair directly with functional teams and use modern coding tools to build the bolt-on utilities that used to take months. In advising, Daniel walked through Tyton data showing students and institutions converging on a blend of human and AI support. The counseling and relationship-heavy work stays human, while scheduling, note-taking, and proactive outreach are strong candidates for AI, freeing advisors for the conversations they got into the profession to have.
Policy is lagging adoption, and the panel was candid that this is now a leadership problem rather than a technical one. With formal guidance still catching up, faculty are left making judgment calls on their own about AI use and academic integrity. Jim distinguished between big-P policy, the slow umbrella framework, and small-P process and procedure that can stay nimble and discipline-specific. Gates closed on a hopeful note about what higher education is actually for. The fundamentals of literacy, critical thinking, and judgment are exactly what endure, and institutions that have always evolved with the culture around them are well positioned to do it again.
If you want to bring a data-driven point of view to AI conversations on your own campus, Tyton Partners' is the place to start. And if you would like to see where you, our three-minute AI fluency assessment gives you a report right away.
