“Artificial intelligence is shaping how many college students think about their academic paths,” said a recently published Gallup article, “College Students Weigh AI’s Impact on Majors and Careers.” Forty-two percent of bachelor’s degree students say AI has caused them to give serious thought to changing their major, including 13% who say they have thought about it a great deal. Even more associate degree students — 56% — say AI has prompted them to reconsider their field of study.
These findings reflect a broader reality: AI is already deeply embedded in higher education, even as many colleges and universities are still struggling to determine how students should use it and how faculty should teach it.
The Gallup article is based on a web survey conducted in October of 2025 by Gallup and the Lumina Foundation among nearly 4,000 US college students pursuing bachelor’s and associate degrees. The results were published in a joint Lumina-Gallup report on AI in higher education.
The survey found that 57% of students already use AI daily or weekly for schoolwork, while only 13% say they never use it. Yet more than half of students report that their institution discourages or outright prohibits AI use in coursework, and 52% say that at least some of their classes lack clear guidance on acceptable AI use.
The findings point to a widening gap between student behavior and institutional policy — one with significant implications for academic integrity, teaching practices, and workforce preparation.
“AI is already embedded in students’ academic lives,” said Courtney Brown, Lumina’s vice president of impact and planning. “Higher education has an opportunity and a responsibility to move from uncertainty to clarity. Students need transparent expectations, ethical guidance and practical training so they can use AI in ways that strengthen learning and prepare them for the workforce.”
The survey uncovered several additional findings that help illuminate how rapidly AI is reshaping higher education.
- Students who use AI for schoolwork most often say they do so to better understand complex course material. Meanwhile, students who avoid AI tools frequently cite ethical concerns or fears that using AI amounts to cheating.
- More than half of students say their schools discourage or prohibit AI use, yet many continue to use the tools regularly despite those restrictions.
- Students also report inconsistent course policies, with over half saying that at least some of their classes lack clear rules regarding acceptable AI use.
- Perhaps most significantly, nearly three in 10 students say their school is not adequately training them to use AI effectively. Students attending institutions that discourage or prohibit AI use are considerably more likely to feel unprepared to use AI in their future careers.
The survey findings are especially important because they align with growing evidence that AI is already affecting entry-level employment opportunities for recent graduates.
For example, “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence,” a November 2025 article by researchers from the Stanford Digital Economy Lab, examined how generative AI may already be reshaping labor markets.
“The proliferation of generative artificial intelligence (AI) has sparked a global debate about its potential impact on the labor market,” the researchers wrote. “This discourse spans utopian predictions of enhanced productivity, dystopian fears of widespread job displacement, and skeptical views that AI will have minimal effects on employment or productivity.”
The Stanford researchers found that while employment for older workers has continued to grow, employment for younger workers has remained nearly flat since late 2022. Entry-level employment has declined most sharply in occupations where AI is automating significant portions of the work.
Employment for workers aged 22–25 in highly AI-exposed occupations — including software development and customer service — declined by nearly 20% between the launch of ChatGPT in late 2022 and mid-2025. Marketing and sales positions also experienced declines, though less severe.
By contrast, employment has remained relatively stable in occupations less exposed to AI automation, — e.g., nursing, psychiatric aides, and home health aides, — where work requires in-person interaction and physical tasks.
In addition, jobs that emphasize human-AI collaboration — including management and repair-related occupations — have actually experienced employment growth, suggesting that AI may increasingly reward workers who can effectively collaborate with intelligent tools rather than compete against them.
Why are younger workers more vulnerable to AI disruption? The Stanford researchers suggest that AI systems are particularly effective at replacing codified knowledge — the formal, structured knowledge acquired through education and training. By contrast, AI remains less capable of replacing tacit knowledge — the experiential judgment and practical know-how accumulated over years of work experience.
“As young workers supply relatively more codified knowledge than tacit knowledge,” the authors wrote, “they may face greater task replacement from AI in exposed occupations.”
A recent New York Times article, “AI Is Coming to Class,” noted that higher education is actively debating how to best incorporate AI into teaching. Some instructors remain strongly opposed to AI tools, while others are experimenting on how to integrate the use of AI tools as part of their education.
The debate over AI in higher education particularly resonates with me because it reminds me of my own early experiences with computers in the 1960s when the legitimacy of using computers as intellectual tools was also in question.
The key event that launched my six-plus-decade involvement with computers took place in the summer of 1962, just before I entered college at the University of Chicago. Planning to major in math and physics, I was looking for a summer job in one of the university’s research labs.
Through a lucky break, I learned that a new computation center was being established at the university. I went over and met its director, physics professor Clemens Roothaan, one of the pioneers in the use of computers in physics and chemistry research. Even though I knew nothing about computers — few high school graduates did in 1962 — I ended up getting a summer job in the brand-new computation center.
I quickly discovered that I enjoyed learning how to program. I continued working part-time at the computation center throughout my college years, and later earned a Ph.D. in physics at the University of Chicago with Professor Roothaan as my thesis advisor.
I used computers extensively in my physics research. As I was finishing my degree, I realized that I enjoyed the computing side of my work more than the physics itself, and in 1970 I joined the computer sciences department at IBM’s Thomas J. Watson Research Center.
In the 1960s, the use of computers for scientific research was still relatively new. Some older physics professors looked askance at the growing use of computers, feeling that this wasn’t “real physics” — meaning the kind of pencil-and-paper theoretical physics they had grown up with over the previous decades.
That reaction strongly echoes today’s debates about the proper use of generative AI tools in higher education. As students grapple with the realities of an AI-augmented economy, many are understandably concerned that colleges and universities are not adequately preparing them for the emerging job market.
The central challenge facing higher education is no longer whether students will use AI. They already are. The real question is whether colleges and universities can adapt quickly enough to help students use these tools responsibly, effectively, and productively.
As happened with computers decades ago, — and with the internet in the 1990s, — AI will eventually become a standard part of intellectual and professional work. Institutions that treat AI primarily as a threat risk leaving students less prepared for a labor market in which human-AI collaboration is increasingly becoming the norm.