Lessons From a Conversation About AI, Future of Higher Ed
Last week in the historic Michigan Union Ballroom, I opened a conversation with a line from The Sun Also Rises that has been echoing in my mind. Nearly a century ago, Hemingway captured a moment when a character is asked how he went bankrupt. His reply: “Two ways. Gradually, then suddenly.”
For years, AI made its way into our institutions through incremental experiments—a pilot here, a classroom tool there. And then, seemingly overnight, higher education found itself confronting large questions at once: What is our core purpose now? How do we teach? What do our students need? What will our graduates face? And how do we lead when the ground continues to shift beneath us?
To make sense of this moment, I convened three remarkable leaders—Amy Dittmar, provost of Rice University; Martha Pollack, president emerita of Cornell University; and Lynn Perry Wooten, president of Simmons University—to join me in an open conversation about how AI is reshaping higher education. I’ve learned from each of them at different points in my career, and it was a privilege to bring them together in Ann Arbor. My role was not to provide answers, but to help surface the insights and questions that leaders across higher education are wrestling with.
Together, the panel offered a rare blend of realism and optimism—an insistence that AI poses meaningful risks, coupled with a deep conviction that the university remains one of society’s most important places for making sense of this future. The conversation moved quickly from concerns about disruption to questions of purpose, responsibility and possibility.
Reflecting on the conversation, five lessons came into focus.
- Opting out of AI is not an option—engagement is part of our mission.
The panelists were unequivocal: Universities cannot sit this moment out.
AI is not something “coming to higher education”—it is something already shaping how students learn, how researchers work and how knowledge moves through the world. To pretend otherwise would be to step away from our responsibility to prepare graduates for professions and communities profoundly affected by these technologies.
But the mandate goes deeper. Universities are among the few societal institutions with the independence and breadth to interrogate AI’s consequences for democracy, creativity, equity, law, culture, labor and human identity itself. Engaging with AI is not an optional enhancement. It is part of the public purpose of higher education. The lesson is clear: our institutions must help shape this moment, not merely adapt to it.
- Collaboration—not competition—will determine whether higher education can meet the challenges ahead.
One of the bluntest observations came when we discussed why universities often struggle to collaborate on AI at the scale the moment requires. The answer was simple: ego. Institutions have long competed—for rankings, for faculty, for funding, for visibility. But that instinct, while familiar, may be one of the sector’s greatest vulnerabilities in an AI era. And while every institution feels these pressures differently, many of the challenges and opportunities are shared across the sector.
No university, regardless of size or prestige, can navigate the demands of AI alone. The infrastructure is costly, the governance is complex and the ethical considerations continue to evolve. At the same time, the societal risks and opportunities extend far beyond the reach of any single campus. Collaboration—across institutions, regions and sectors—is not merely helpful but increasingly essential.
The panel emphasized the promise of multi-institution research partnerships, shared pedagogical approaches, regional collaborations on AI infrastructure and carefully constructed public-private partnerships that preserve academic values. The message for higher education is clear: Our future capacity hinges as much on our willingness to act as an ecosystem as it does on our ability to innovate locally. The questions ahead are too big, too urgent and too interdependent for any institution to answer on its own.
- AI is pushing universities to elevate—not diminish—the human dimensions of education.
Contrary to fears that AI will replace the human relationships that define learning, the panel suggested that AI is actually clarifying what is distinctly human about education.
As AI takes on more routine tasks—drafting materials, sorting information, offering basic guidance—the role of faculty and staff becomes even more concentrated in the aspects of learning that depend on human connection. Students continue to seek mentorship, community, discussion, intellectual challenge and the chance to build judgment in dialogue with others. Rather than reducing the need for faculty, AI places greater emphasis on the meaningful interactions students cannot find elsewhere.
The panel made the case that while the transactional elements of education may increasingly be automated, the relational elements are becoming more vital than ever. The path forward calls for learning environments intentionally designed to ensure that technology expands human connection rather than encroaches on it. In an era when pressures related to cost and scale are intensifying, the value of human connection becomes not an inefficiency to eliminate, but an asset to strengthen.
- Leading in an AI era requires institutional nerve: more experimentation, less perfection.
Higher education is not often rewarded for speed, but this moment requires measured boldness. The panel noted that universities will need to cultivate a different posture—one that embraces experimentation without abandoning rigor.
Responsible leadership in an AI era means creating conditions where faculty and staff can test ideas, explore new tools and learn from failures. It means offering professional development that keeps pace with the technology rather than trailing behind it. And it requires administrators to resist the desire for perfect clarity before taking action. Universities that wait for certainty will find that decisions have already been made for them—by industry, by markets or by the accelerating technology itself.
The panel encouraged institutions to embody the very qualities they try to cultivate in their students: curiosity, adaptability, intellectual humility and a willingness to learn through practice. Comfort cannot guide us through a moment defined by uncertainty; confidence and curiosity must take its place.
- The future will be shaped by humanists and technologists working together.
A final theme that emerged was the essential role of interdisciplinarity. AI is not simply a technical challenge; it is a societal one. Questions of meaning, identity, justice, governance and values are as central as questions of models, computers or data. The panel emphasized that the humanities have a vital role to play in this moment, not in resisting technology but in contextualizing it.
Their expertise in ethics, interpretation, culture and human behavior offers perspectives that purely technical fields cannot supply. At the same time, disciplines grounded in technology, science and quantitative reasoning bring capabilities the humanities alone cannot offer. The future will depend on scholars and practitioners who can bridge these domains rather than reinforce the boundaries between them.
The panel’s message was clear: The most consequential work ahead will happen at the intersections, where human imagination and technological possibility meet. Preparing students for this future will require educational experiences that refuse to silo technical fluency from ethical judgment or creative thinking from computational reasoning.
Where We Go From Here
If Hemingway was right that change arrives “gradually, then suddenly,” then higher education is now navigating the “suddenly.” The foundations have been shifting beneath us for years, but the acceleration we’re experiencing now is unmistakable. The pace is different. The risks are sharper. And the questions confronting us—about purpose, responsibility and the future of human connection—feel larger than anything we’ve faced in recent memory.
AI forces us to look closely at what higher education is for. It invites us to reconsider how knowledge is created and shared, how learning happens and how we build trust in a world where the boundaries between human and machine expertise are increasingly porous. In many ways, AI doesn’t just challenge higher education—it reveals the work only higher education can do.
We may be entering this moment suddenly, but we are not entering it unprepared. Universities remain one of the few places capable of engaging the full spectrum of what AI represents: the promise, the peril and the profound questions about what it means to learn, to teach and to be human. Whether this becomes a moment of disruption or one of reinvention will depend on how we choose to respond—together and with clarity about the mission that has always defined us.
