Earlier this year, Microsoft founder Bill Gates warned that AI could soon render humans unnecessary “for most things.” While the claim struck us as alarmist, recent data from the World Economic Forum suggests it may not be far off base. More than 40 percent of employers in the report plan to reduce their workforce as AI expands across industries, and an estimated 92 million jobs will be displaced by technological advancements over the next five years. But, just as importantly, AI is expected to create 170 million new jobs. The question isn’t whether jobs will exist, but whether students will be ready for them.
On most campuses, students and faculty are experimenting with generative AI tools on their own while colleges still debate policies in committee. Institutional processes built for careful deliberation across departments, accreditors, and faculty senates are not designed for the current pace of technological change. Research suggests that nearly 40 percent of workers’ current skill sets will be transformed or rendered obsolete within the next five years. This year’s graduating class started college before ChatGPT even existed. Now, generative AI and other similar advances in technology are rewriting job descriptions, reshaping entire industries, and redefining what it means to be career-ready.
This moment demands a fundamental shift. While the example is not without controversy, there are lessons we can learn from “Operation Warp Speed,” an approach the federal government took to accelerating vaccine development during the pandemic.
Before 2020, vaccine development took at least a decade. But facing a global crisis, researchers, regulators, and funders tore up the playbook. They ran trials in parallel, accelerated manufacturing, and cut through red tape to deliver a life-saving innovation in record time. It’s an approach higher education can learn from to equip students with the skills they’ll need to thrive in an AI-powered world.
Preparing students for this future requires a rapid reevaluation of what it means to be “career-ready” in an era when generative AI is a part of nearly every industry. Students need fluency in the capabilities and limitations of current tools, as well as an awareness of how AI is transforming their chosen fields. Just as importantly, they need to further hone human, soft skills that machines can’t replicate. Today, very few institutions are building this foundation into the student experience in a coherent, intentional way.
Some have started, however. At the University of North Carolina, for example, a faculty-led pan-university task force has moved quickly to establish AI guidelines, build a community of practice, collect metrics on AI usage, launch an online hub for faculty, staff, and students, and support the rollout of an AI Acceleration Program.
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Meanwhile, at the University of Alabama, a cross-campus task force led by the Office of Academic Affairs developed clear AI guidelines for teaching and research. The task force’s work includes faculty training on AI’s practical and ethical uses, an AI fellowship program to help integrate the technology into coursework, and plans to launch new undergraduate and graduate degree programs in AI this year.
These efforts prove that agility is possible, but only with the right structures and leadership in place. The traditional, well-intentioned approach to decision-making in higher education—where responsibility is distributed across departments and innovation is often stymied by approval cycles—doesn’t match the moment.
A “warp speed” approach to academic innovation requires a strategy that can be implemented immediately and scaled for long-term impact across teaching, research, and operations. In the short term, universities can embed foundational literacy around AI concepts, ethics, and technology directly into the student journey by integrating these critical competencies into freshman orientation and the core curriculum. This ensures all incoming students, regardless of their chosen discipline, develop a baseline mastery of the AI tools rapidly remaking their future.
The goal is to ensure students develop reflexive AI habits, turning to AI as a first step in arenas where it is allowed and instinctively asking how technology can help them solve a problem just as naturally as they’d reach for a pen to write something down. As Shopify CEO Tobias Lutke recently wrote, “reflexive AI” is becoming a standard expectation for employers.
Once students move into their majors, they need to learn how AI is being used in their discipline. A business school student might learn how AI is changing marketing while an archeology student might learn how AI is being used to find ancient artifacts. These courses should prepare students to critically evaluate AI’s capabilities, risks, and ethical implications in their future careers, giving them the tools to not just use AI, but to question, shape, and guide its role in society.
To make this shift, faculty need to rethink their role as educators. An internal UNC survey found that 95 percent of faculty agreed its graduates must “be prepared to use AI tools effectively, ethically, and critically” and three quarters agreed it was the role of faculty to ensure that happens. This demands a reimagining of assignments to uphold academic integrity, blending new tools with traditional methods like Blue Books, whose sales are surging. While AI makes information easily accessible, students still need deep domain knowledge to frame those questions thoughtfully and evaluate the answers AI provides. In the age of prompting, Roger Bacon’s insight—“to ask the proper question is half of knowing”—rings truer than ever.
Colleges won’t succeed by wedging AI into old structures but by fundamentally redesigning them. It’s the difference between trying to force a pump dispenser into a bar of soap versus designing liquid soap in a bottle.
Researchers and policymakers didn’t create a COVID vaccine by following standard procedure. They did it by recognizing the world had changed and by responding with unprecedented urgency. As AI reshapes the economy, the labor market, and the nature of knowledge itself, higher education will need to do the same.
