Are You Ready for the AI University?

We are awash in predictions about the impact of artificial intelligence on higher education. These accounts differ wildly in their prognoses but share the assumption that AI is not going away, and is likely to upend every facet of how universities function. Enrollment managers will use it to increase yields; counselors will rely on it to address student mental health; student advisers will use it to boost retention; and financial analysts will use it to model and mitigate risk. It should go without saying that AI will continue to insert itself into the classroom, forever altering the relationship between students and professors.

The academy has chiefly responded to the initial stirrings of this revolution by getting mired in a tired debate about academic ethics. Students cheated before the advent of AI, and they will continue to cheat for years to come. Even if a new app could detect and prevent all AI-enabled student work, it would be inconsequential to AI’s inevitable spread throughout higher education. If your interest in AI doesn’t extend beyond cheating, you’re missing the bigger picture.

An AI arms race is underway. In a board room at every major college in America there is a consultant touting AI’s potential to lower costs, create new markets, and deliver more value to students. In that same board room is often a president or chancellor who has had to trim budgets and cut jobs. If the consultants aren’t on your campus yet, they’re coming.

The early adopters of AI are the usual suspects: the Ivy League, premier public universities, and elite liberal arts colleges. Across the country some institutions are already piloting fully AI-instructed courses and utilizing AI to enable higher yields and improve retention, graduation rates, and job placement. Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots. Sadly, institutions that need AI the most, such as community colleges and regional public universities, will be the last to get it. Prepare for an ever-widening chasm between resource-rich, technologically advanced colleges and those that are cash-starved and slow to adapt to the age of AI.

Savvy campus leaders are already promoting their institutions as AI-enabled or AI-driven; in the next decade, AI will become central to these institutions’ brands, like a lazy river or a winning football team. Colleges that extol their AI capabilities will be signaling that they offer a personalized, responsive education, and cutting-edge research that will solve the world’s largest problems. Prospective students will ask, “Does your campus offer AI-taught courses?” Parents will ask: “Does your institution have AI advisers and tutors to help my child?”

In the movie Blade Runner 2049, one of the characters (coincidentally an AI humanoid) says about the rise of AI: “You can’t hold the tide back with a broom.” We are at a tidal moment.

What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.

Film photography is the best example of creative destruction in our lifetime. Remember taking a picture with film? Nostalgia aside, it was inflexible, inefficient, and costly. We bought 24-exposure film for $4 and had it developed for $10. At the end of the process, we were lucky to get three or four worthwhile pictures. The rest were out of focus, off-center, or poorly lit. The advent of digital photography exposed the deficiencies of film. Creative destruction transformed photography into a more efficient industry that delivers infinitely more value.

The same dynamic is taking root in higher education.

Colleges have traditionally relied on economies of scale to maintain their bottom lines. With labs, dormitories, lecture halls, athletic facilities, and so much else, colleges have exorbitant fixed costs. Those fixed costs have typically been covered in large part by student enrollment. Now that enrollment is declining, higher education’s cost curve is breaking. No amount of cutting will fix the underlying problem. Many colleges have masked their operating deficiencies by using Covid-relief funds in the past few years, but now, with those funds exhausted, they are dealing with a broken economic model. The Trump administration’s cuts to research funding are adding additional stress to colleges’ already precarious cost structure.

More damaging than the cost curve is the shift in how students view the value of higher education. Having grown up with Amazon, Netflix, and Google, students expect a speedy, on-demand, and low-friction experience. Moreover, they increasingly view college through a transactional lens: They pursue a degree to get a job. So they regard college much like any other consumer product, and like those other products, they expect it to be delivered how they want, when they want. Why wouldn’t they?

Over the next decade, through attrition and displacement, AI is going to decimate faculty ranks. For most institutions, one-third of their underlying cost structure is comprised of faculty-related instruction. For years now, administrators have been trying to reduce faculty costs by hiring adjuncts and nontenured instructors, increasing class sizes, and developing online models with fewer fixed costs. Now they have AI, which can deliver more value at lower cost.

Expect more asynchronous, AI-led courses in all disciplines. When students are given a choice between an AI-taught virtual class with a high degree of accessibility and personalization or a brick-and-mortar, human-taught class at the same time every week with little or no flexibility, which will fill up first? (Actually, it’s a trick question: The AI class has unlimited capacity — it can’t fill up. Another advantage.)

The big mistake faculty members make is underestimating the existential threat AI represents to their livelihoods. Professors need to dispense with the delusional belief that AI can’t do their job. Faculty members often claim that AI can’t do the advising, mentoring, and life coaching that humans offer, and that’s just not true. They incorrectly equate AI with a next-generation learning-management system, such as Blackboard or Canvas, or they point out AI’s current deficiencies. They’re living in a fantasy. AI is being used to design cars and discover drugs: Do professors really think it can’t narrate and flip through PowerPoints as well as a human instructor?

As with other IT applications on campus, such as data storage and enterprise resource planning, colleges will rent capacity and processing from third-party providers such as OpenAI or Salesforce. Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.

Importantly, AI will not only replicate the current learning approach. It will draw from all course sections on campus and correlate course pedagogy with student performance. By extension, it will develop the “best practices” in a discipline as a means for better understanding educational approaches that yield better student outcomes such as retention, degree progress, and graduation. AI will undertake a process of continuous learning and improvement to ensure a personalized student experience. Two students might both be enrolled in Greek History 1010 in the same semester, but they won’t be taking the same class: It will be entirely tailored to their learning styles. Today, such AI capabilities are already a reality.

AI’s destructive path through higher education is easy to map out. The impact will initially fall on postdocs and teaching assistants. AI teaching assistants are already gaining traction in K-12 education; college is next. A dean at Boston University said the quiet part out loud when he suggested that AI might replace striking graduate students. While the comments were quickly retracted, the specter remains.

Teaching assistants and graduate assistants will be the first casualties of AI displacement. Then, as AI becomes capable of teaching full-blown courses, colleges will cull their nontenured faculty ranks. Once AI exhausts efficiency gains in those areas, it will set its sights on tenured faculty. Will anyone be safe? Late-career professors will likely make it to retirement with only minor disruption. AI initiatives already underway will likely take two to three years to be implemented. If we factor in the (short-term) reality that some students still prefer a human-to-human class, savvy full professors will likely be able to patch together another 10 years or so in which their pedagogical reality looks similar to when they entered the professoriate.

However, when those full professors retire, AI-fueled faculty attrition will begin. There are about 200,000 full professors at American colleges — about a quarter of the professoriate. Their retirements may generate promotions, but they won’t generate new lines. Instead, AI will take over those sections, and these jobs will be lost forever.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom. How does AI alter how we teach engineering? Or pursue basic science? AI’s impact will vary widely across disciplines, but all will be affected. In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course. While students will readily accept non-human professors, any new technology will have “hiccups” that will require human intervention to resolve. Once the training wheels are off, AI-taught courses will become the dominant paradigm.

Beyond the classroom, researchers will benefit exponentially from AI. It is bound to accelerate discovery and innovation. In labs, AI will boost productivity, reduce errors, and make important linkages between domains. AI will write and administer grants, leaving more time for actual research. Grantmaking agencies, such as the National Institutes of Health and the Department of Defense, will explicitly seek out AI-enabled research projects.

As with any process of creative destruction, many of academe’s practices, processes, and institutions are bound to disintegrate. Already, applications such as ChatGPT’s deep research are providing glimpses into the future. At a base level, AI is being used extensively to compile literature reviews in seconds, a task that until recently took hours upon hours. Soon it will be able to render that information to develop hypotheses, scrape data, and write a full-fledged academic paper in minutes. All of this puts into question what, exactly, will constitute doctoral training in the future. It’s likely that in just a matter of years many of them will be obsolete. Expect a significant culling of doctoral programs worldwide.

I can think of no plausible scenario in which there will be an equal number of faculty members in 10 years as there are today. Will there still be human-led instruction in some places? Of course. We still have record shops and drive-in movie theaters. But they are vestiges of how things were, not a reflection of actual market preferences.

Last year, I sat in a faculty meeting while a guest lecturer gleefully explained how they had used AI to design their class, craft PowerPoint presentations, and develop exams. At the end of the presentation, a colleague leaned over and asked, “Then what’s our job?” I have thought long and hard about that question. If faculty hope to survive, much less prosper, in the age of AI, they need to come up with a compelling answer to that question: “What’s our job?”

What about students? How will AI change their experience? Many colleges are already incorporating AI bots, such as ChatGPT, into classrooms to address rudimentary, standardized tasks. AI bots are also doing research, conducting statistical analysis, writing papers, preparing presentations, and other familiar duties.

In the near future, if a student misses class, they will be able to watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

The ultimate transformation will occur when students begin to work with AI agents. Think of voice assistants like Siri or Alexa, but on steroids. Sam Altman, chief executive of OpenAI, described agents as a “super-competent colleague that knows absolutely everything about my whole life, every email, every conversation I’ve ever had, but doesn’t feel like an extension.”

Today, most students attend summer orientation, meet their roommates, and leave with a T-shirt. By 2030, incoming students will also be given a personalized AI agent. Similar to how you might ask Alexa to play a song, students will ask their AI agent to prepare a course schedule, stay on top of their assignments, find a job opening, apply to graduate school, and manage their mental and physical health.

Picture this: Students will no longer sign up for courses; they will work with their AI agents to build personalized instruction. A student who requires a biology course as part of their major won’t take the standard three-credit course with a lecture and lab that meets for 14 weeks with the same professor. Instead, the student will ask their AI agent to construct a course that transcends the classroom, campus, and time. The AI agent would find expert scholars across the globe, line up real-time or recorded video lectures, and simultaneously incorporate material from YouTube, Google, and university libraries. If the AI agent can’t find lab space on campus, it will help find a lab with capacity halfway across the world and enable the student to participate using an augmented-reality headset. AI agents that have evolved with a student throughout college will be able to design assessments that reflect that student’s learning style, ensuring they have achieved fluency in the subject.

By the end of the decade, AI agents will incorporate avatars. Think about the way an iPhone recognizes facial characteristics to unlock itself. Now imagine AI avatars that will be able to sense subtle facial expressions and interpret their meaning. If during a personalized lecture an avatar senses on a student’s face, in real time, that they’re frustrated with a specific concept, the avatar will shift the instructional mode to get the student back on track.

AI agents will allow for truly lifelong learning. Undergraduates will be able to take the entirety of their college education with them on a portable, scalable blockchain — every syllabus, every text, every assignment, every interaction with every professor, every grade, every lecture, every experiential activity, every email — and an AI agent that can mine that vast repository as needed. Imagine instantaneously asking your AI agent to call up a lesson on tax accounting or nursing that you took five years earlier. If the lesson has become outdated, the AI agent can provide updated material and even offer new mini credentials to validate that you’re up to speed.

While students will gain the most from AI, and faculty will need to adapt to its disruptive capabilities, it will also dramatically alter higher-ed functions across the board.

If we look at day-to-day operations at the average college, AI will first disrupt the registrar. Classroom scheduling and capacity management will be entirely automated — well beyond the current system of Excel spreadsheets that most institutions still employ. Student records will be entirely managed by AI using blockchain, and they will be owned by the student and empower the student. Gone will be the days when universities held students hostage by not sharing their student records. Similarly, student credit transfer — long a bane of most institutions — will be entirely automated. AI will “read,” evaluate, and award the appropriate amount of student credit. AI will also streamline and automate student financial aid at the institutional level.

For the past decade, enrollment professionals have been seeking the elusive holy grail of enrollment management: one-on-one targeted marketing to prospective students. AI will help realize this vision. Currently, enrollment officers employ crude modeling and customer relationship management tools to target students. Instead of targeting a group, high school, or town, AI will filter prospective students by attributes that play to an institution’s strength. AI bots will reach out to them and facilitate one-on-one recruitment conversations that produce a much higher yield rate. Enrollment professionals will need strong AI fluency to maintain their jobs.

If you work in career services, AI will soon automate every aspect of your role. Today, even rudimentary AI can do most career-services functions, including résumé writing, job searching, and interview coaching and preparation. After reading this, career-services professionals will offer up a rebuttal: “Our students want to deal with a human career-services professional!” No, they don’t. Human interaction is not as important to today’s students. Moreover, AI can assist thousands of students simultaneously; the average career-services professional can help a dozen students on a good day.

Other administrative functions such as accreditation will also be fully automated. In our unquestioning march to assessment that is driven by standardized processes and outcomes, we have laid the groundwork for AI’s ascendancy. Did the student learn? Did the student have a favorable post-graduation path, i.e., graduate school or employment? Accreditors will have no choice but to offer a stamp of approval even when AI is doing all the work. In the past decade, we have shifted from emphasizing the process of education to measuring the outcome of education when determining institutional effectiveness. We have standardized pedagogy, standardized student assessments, standardized teaching evaluations, and standardized accreditation. Accreditation by its nature is standardized, and we won’t need vice provosts to do that job much longer.

Nor will chancellors, presidents, provosts, and deans be immune to AI’s disruption. Major organizational decisions related to expanding into new markets, building new laboratories, launching new programs, increasing housing capacity, investing in athletics and student life, and allocating resources will all be made with the guidance of AI. We are already seeing CEOs relying on AI for data-driven, resource-intensive decisions in industries far more complex than higher education, such as the life sciences, health care, and defense.

As political pressure on higher education continues to instensify, trustees and overseers will increasingly ask, “Did you run this through AI?” or “Did the AI engine arrive at a similar decision?” Governance bodies at institutions will want to see both the human and AI rationale for the basis of many decisions. By 2030, most institutions will rely on AI to be part of every major decision on campuses.

All the preceding envisions a future where AI works within the boundaries of the existing higher-education structure. But that is only step one of a broader transition. Imagine a university employing only a handful of humans, run entirely by AI: a true AI university. In the next few years, it’s likely that a group of investors in conjunction with a major tech company like X, Google, Amazon, or Meta will launch an AI university with no campus and very few human instructors. By the year 2030, there will be standalone, autonomous AI universities.

AI U will have quite a simple organizational structure. It will have an office of academic affairs with a seasoned provost and team. They will select a tight set of academic disciplines that lend themselves to the early-stage capabilities of artificial intelligence, such as accounting or history. As illustrated earlier, academic departments will have human chairs who will manage AI agents within each discipline. Students will earn credits toward professional credentialing, such as accounting, or full-blown degrees, based on their timing and needs. The institution will deliver a high level of personalized and flexible instruction.

Will AI U succeed? As with the dot-com era, out of the gate there will be hundreds of AI university startups — the vast majority will fail, as with any wave of innovation. However, dozens of AI universities will survive and prosper and exist side by side with today’s institutions. The AI university will be ideally suited to nontraditional students who have not been well served by the “one size fits all” pedagogical model that has dominated higher education since its inception. AI U will target the “degree completer” market: the 40 million Americans with college credit but no degree. For the past decade, higher education has been chasing this elusive market to no avail. We have been trying to put a square peg into a round hole. AI U will help these individuals complete their degrees.

AI universities will have a significant cost advantage over traditional or AI-empowered universities. We witnessed a similar dynamic relative to online learning. One of the reasons that institutions such as Southern New Hampshire University and Western Governors University have risen to such dominance in the past decade is that they operate on a different financial model. They do not have to cover acres and acres of nonproductive assets, such as classrooms that sit empty half the year; instead they can shift cash flow to further investments or lower tuition. In theory, AI will significantly reduce the cost of college. As a result, most AI U students will graduate with little to no debt.

Will traditional universities survive? Absolutely. Millions of students will continue to want an old-fashioned college experience complete with dorm rooms, a football stadium, and world-class dining. However, these experiences are not mutually exclusive: Even these tradition-bound institutions will employ AI. The market expectation will be that top-tier institutions will provide both an unparalleled student experience and AI-empowered education.

Predicting AI’s disruption is the easy part. The tough part is making people realize the inevitable. The temptation is to sugarcoat what’s in store. But that doesn’t help anyone prepare for the pain that will accompany this inevitable transformation.

Will students benefit from AI? From their perspective, tremendously. Will there still be professors? Yes, but fewer of them, and those who remain will need to be technologists as much as they are scholars. Will jobs be lost? Yes, sadly and permanently.

Will some disciplines benefit from AI’s emergence? Certainly, we can predict benefits for the usual suspects such as computer science, data science, and mathematics. However, I think there may be a silver lining for the humanities. For all the talk about the decline of the humanities and its values as AI fully assimilates itself into society, the ethical, moral, and legal questions will bring the humanities to the forefront. Engineers can help AI understand standardized processes and systems, scientists can develop and evolve AI, and businesspeople can help understand the bottom line, but who will help AI understand its place in the world? If technologists and business professionals are AI’s disciples, humanities scholars must be its conscience.

None of this can happen, though, if professors and administrators continue to have their heads in the sand. For everyone who works in higher education, there is a great deal of pain and disruption to come. We can minimize the damage, though, by helping people understand how AI will transform higher education. Uncomfortable as they are, these are the conversations we need to start having if we want to be ready for what’s coming.