It's Time for Higher Ed to Get Serious About AI Strategy
- By Yolanda Watson Spiva
- 05/18/26
Three years after the public release of ChatGPT, despite all the hue and cry about generative artificial intelligence destroying writing, disrupting classrooms, and heralding the collapse of teaching and learning as we know it, the education sector simply can't get enough of this technology.
A recent Microsoft report found that education has the highest AI usage rate of any industry, with nearly nine in 10 education institutions globally reporting that students, instructors, and campus leaders are using generative AI. On college campuses in the United States, AI usage has far outpaced efforts from policymakers and institutions to guide or regulate it. The latest Educause survey of higher education's AI landscape found that fewer than 60% of institutions consider AI to be a strategic priority and that less than 40% have policies on acceptable AI use.
While there's a growing recognition of AI's importance, many institutions still lack a clear roadmap for harnessing this technology to improve student outcomes. It's not just building the plane while flying it. It's taking off without knowing where you're going — or where you might land.
It's ironic that the nation's colleges and universities have had so much difficulty coming to terms with AI. Higher education didn't just study artificial intelligence. It invented it. The earliest AI breakthroughs emerged in the mid 20th century from university research labs, where computer scientists sought to replicate human reasoning through logic, mathematics, and language.
From early neural network models at Cornell and MIT to natural language processing research at Stanford and Carnegie Mellon, academic discoveries laid the groundwork for everything from search engines to speech recognition. The transformer architecture that powers ChatGPT and other large language models originated from Google researchers building on decades of publicly funded academic work in machine learning and linguistics.
That these groundbreaking discoveries emerged from American universities should come as little surprise, as some quarters of higher education have long embraced an ethos of experimentation and innovation. But the higher education ecosystem is also beset with fragmentation that often produces incoherent results. The recent bankruptcy of the ed tech conglomerate Anthology illustrates how a tightly controlled, top-down approach can backfire. But moving to an anything-goes approach is just as perilous. Without a coordinated strategy that involves multiple academic and administrative units across the entire campus, colleges risk wasting resources, duplicating efforts, and ultimately failing to deliver on the promise of deploying technology to improve learning and operations.
Some pioneering institutions are taking a broad approach to AI. They are increasingly experimenting with developing AI literacy at scale, funding programs for classroom innovation, and embedding AI into curriculum and instruction. Rather than restricting these efforts to department, division, or function, they are fostering interdisciplinary and institution-wide collaboration and building an infrastructure of targeted initiatives across their systems to increase access, support faculty, and improve student success.
Arizona State University has emerged as a national test case for how universities can integrate AI into teaching and research at scale. While many universities moved to restrict or ban ChatGPT, ASU moved first — becoming the first to strike a campus-wide deal with OpenAI. The university launched its AI Innovation Challenge in 2024 to give faculty, staff, and students a structured way to experiment with generative AI in teaching, learning, and research. Selected projects were developed in a secure environment with support from ASU's technology team, helping the university identify priority areas for investment. The effort has already produced custom AI tools and insights that are shaping how ASU scales innovation across campus.
Other institutions are taking a broader approach to AI literacy, ensuring students across disciplines gain a shared foundation in the technology. The University of Louisiana System launched its Empowering AI Literacy microcredential in 2024 to ensure that all of its 82,000 across all nine system campuses students gain foundational AI knowledge. The free, self-guided program gives students the opportunity to begin building skills directly applicable to AI roles and AI-driven industries. Instead of teaching about specific AI tools, the course covers broad AI concepts underpinning the technology and explores its impact on education, work, and society to ensure that the content remains relevant as the technology continues to evolve.
Some institutions are linking AI education directly to work-based experience. At City Colleges of Chicago, faculty are working with employers in sectors like healthcare, logistics, and business to design projects where students use AI to solve real-world problems in concert with employers. As part of the AI Readiness Consortium — a partnership between Complete College America and Riipen — the initiative helps students build practical AI skills while earning credit toward their degrees and gaining experience that connects classroom learning to career pathways.
The technologies now reshaping the world were born from the same spirit of curiosity, experimentation, and openness that defines higher education. Yet as colleges and universities increasingly adopt AI tools, they risk losing sight of that lineage. But if institutions can skillfully and intentionally deploy AI on their campuses, they can help students stay on track and thrive. Without thoughtful coordination, colleges and universities might find themselves relying on technologies it helped create but no longer fully understand or control. The good news is they still have ample time to author their own destiny and ensure students, as well as administrators, have the skills and tools to harness AI's fast-changing potential.