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Commencement season is in full swing. It is a joyous time for graduating students and their families, and it is also a moment of genuine achievement for the colleges and universities, faculty, and staff who helped make this milestone possible. Yet this year’s celebrations are taking place in a world dramatically different from the one many graduates entered when they began higher education. Geopolitically, economically, technologically, and politically, the changes have been profound. The ground has shifted beneath higher education, even if many institutions have not yet recognized the full scale of the transformation already underway.
An age of AI-enabled higher education has dawned. That development cannot be undone. The question is no longer whether AI will reshape higher education, but whether colleges and universities will shape that transformation in ways that advance their missions and better serve their students. In the coming years, the magnitude of this change will become fully evident. Institutions that treat AI as a passing trend or a peripheral tool will fall behind. Institutions that use it to reimagine learning, support, access, and outcomes will define the next era of higher education.
In this new age, the long-term value of a college or university will be determined by how well it improves the lives, learning, confidence, opportunities, and outcomes of its students. Students have always been the heart and soul of any great college or university. What is changing is the level of accountability institutions will face for serving them well. Prestige, tradition, and rankings will matter less if students, families, employers, and policymakers cannot see clear evidence of student success. The value of institutions will increasingly be measured by how effectively they help students learn, persist, graduate, and thrive after graduation.
That shift has major implications. Barriers to student success, including persistently high DFIW rates, should be understood as symptoms of institutional failure, not merely student shortcomings. AI now makes it possible to dramatically expand guidance, feedback, personalization, simulation, tutoring, writing support, research assistance, career exploration, and lifelong learning. In that context, continued tolerance of high failure, withdrawal, or non-completion rates will become increasingly difficult to defend. Students have a right to expect serious support for success. If existing pedagogical practices cannot help all students who make a good-faith effort succeed, students will reasonably ask why better technological and instructional alternatives are not being pursued.
The colleges and universities that thrive will be those that offer students deeply personalized learning experiences, proactive and effective support, meaningful experiential opportunities, and strong post-graduation outcomes. This will matter even more as the pool of traditional high school graduates shrinks and public skepticism about the value of higher education remains high. Institutions that can clearly demonstrate student learning, affordability, belonging, career preparation, and life-changing outcomes will rise above the noise. Their value proposition will be evident not because they claim excellence, but because students experience it and outcomes confirm it.
As AI’s capabilities grow, institutions should seize the opportunity to redesign the student experience rather than merely layer AI onto old, inefficient policies, processes, and practices. AI can already provide 24/7 tutoring, practice questions, formative feedback, study planning, and academic coaching. It can help students understand degree requirements, compare pathways, and navigate academic options. It can identify students who need support before they miss class, fall too far behind, or stop attending altogether. It can help students develop resumes, practice interviews, create professional portfolios, and engage in simulations that approximate entry-level work experiences. It can also empower faculty by supporting the development of rubrics, practice problems, differentiated materials, examples, and assessments. Used wisely, AI can strengthen teaching and learning while also reducing costs, including the heavy burden of expensive textbooks.
Much as the Internet created fertile ground for experimentation in the mid- and late-1990s, AI now creates a similar moment for higher education. Colleges and universities should undertake bold, disciplined experiments with AI. Some initiatives will succeed. Others will fail. Both will produce valuable lessons. But experimentation must be connected to mission, evidence, and student outcomes. The goal is not to appear innovative; the goal is to become more effective at helping students succeed.
In Spring 2026, the question “How can we add AI to higher education?” is already outdated. That was the question of 2023 and 2024. The better question now is: “Knowing what AI can do, what would we build differently if we were creating a truly student-centered institution today?” The opportunity is large, and the risks are real. But starting with the student and working backward offers the surest path forward. It allows colleges and universities to build for the long term while remaining faithful to their vital academic missions.
