Students are trying to figure out how to incorporate artificial intelligence into their choice of major.
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Midway through his master’s degree in computer science at Stony Brook University, Murtaza Mister realized that the job market he was preparing for was changing in real time.
After applying to more than 3,000 jobs and internships during his time at school, the 23-year-old began to notice that employers were no longer just asking for traditional computer science skills. “I’ve seen job descriptions evolve from asking for computer science basics to being able to use AI tools and then building with AI tools,” he says. “Halfway through my master’s, I realized that I also needed to add this layer to my current portfolio.”
Students across the country are making similar evolving calculations as artificial intelligence reshapes the way they think about majors, careers and the value of college itself. A new one Lumina Foundation-Gallup survey of more than 3,500 students pursuing a bachelor’s or master’s degree found that 47% had considered changing majors because of AI, either “a lot” or “a fair amount.” The most likely to have considered it were those in technology fields, with 70% having this level of thinking. The least likely to consider a change? Students studying the natural sciences and training for the health care professions, which not so coincidentally have been the fastest growing areas of employment recently.
“Students are not waiting for the future of work to come,” says Courtney Brown, vice president of impact and planning at the Lumina Foundation and the study’s lead researcher. “They’re trying to respond to that now and figure out what’s best.”
This is clearly better than doing nothing. But Brown suggests taking a longer-term, broader view when deciding what to study.
1. Don’t kid yourself about “AI-Proof” careers.
Many students are justifiably trying to determine which career fields might survive AI disruption. (A recent one Stanford University The study found that employment is declining among younger workers in occupations highly exposed to genetic AI.)
But Brown cautions that students may overestimate a degree’s ability to “future-proof” it. “I don’t think there’s a winning lane,” Brown says, comparing the students’ dilemma to trying to pick the fastest-moving line at a grocery store. “All lanes will lead to AI, which will have an impact on each main. It’s just a timing difference.”
Instead, Brown says students should think about how artificial intelligence can change work opposite occupations.
2. Look for specialties that combine human skills and techniques
Students increasingly need programs that combine technical fluency with what employers still struggle to automate. Even students immersed in artificial intelligence worry about over-reliance on technology. “As humans, we’re always wired to find the easiest way to deal with a problem,” says Mister.
“The important thing is to look for majors that combine technical skills with distinctly human abilities, such as communication, creativity and problem solving,” says Brown. (Some examples he gives: business analytics, industrial engineering, public health, architecture, environmental studies, cognitive science, and digital media or game design.)
Brown says these “hard” people skills are often taught in higher education, but not well explained in terms of career relevance: “Until you graduate and look for a job, no one helps you communicate or translate [these skills] in the world of work”.
At the same time, Brown says she’s seeing students increasingly combine the humanities and social sciences with digital and artificial intelligence disciplines, rather than abandoning the humanities altogether. There is evidence that in the past, at least, college graduates with majors in two different fields were much less likely to experience career shocks such as long periods of unemployment.
3. Pay attention to whether colleges actually teach artificial intelligence
While college AI cheating has gotten a lot of attention, Brown says universities are increasingly concerned about a different malaise: AI addiction. “The challenge for institutions is to find the balance between protecting core learning while also preparing students to work effectively with AI,” he says.
Many universities still lack clear guidelines, and more than half of participants in the Lumina and Gallup survey said at least some of their classrooms lacked clear AI rules.
Brown argues that colleges should help students understand responsible use, deep fakes, ethical concerns, and how AI should “complement and not take over what humans need to do.”
Meester saw this tension firsthand while serving as a teaching assistant for a distributed systems course at Stony Brook. Students were allowed to use AI to help write code, he says, “but then you have to own the code, you have to understand what the code does, and you have to know the concept behind it.”
As a TA, he assessed the students through personal interviews where they had to explain the concepts behind their projects.
4. Look for colleges that incorporate career guidance earlier
Many students receive little meaningful career guidance until they approach graduation. “The career services office shouldn’t be where you visit the last week before graduation,” says Brown.
Instead, he suggests, career advice should start from day one and help students understand how what they’re learning connects to the evolving demands of the workforce. “Career guidance needs to evolve faster than it is,” he says.
This may matter even more as families increasingly question the return on investment of college. (It’s not just career counseling that matters. Schools that promote internships and work experiences are worth considering, too.)
5. Don’t mistake AI avoidance for AI readiness
If colleges treat AI as a tool to be avoided, they may be putting students at a disadvantage.
“We’re doing ourselves a disservice if we try to put it in a box and say AI is over and we’re not using it, when it’s a reality we’re all experiencing and it’s going to be the reality of the workforce,” Brown says.
He recognizes that many institutions are struggling to keep up with the pace of change. But colleges that fail to adapt quickly enough risk being left behind by students already trying to navigate an AI-driven economy on their own.
“Institutions that aren’t nimble, that aren’t able to move fast enough, are the ones that will be left behind,” he says.
In the age of artificial intelligence, students may be better served by looking less for “safe” majors and more for programs that teach adaptability, critical thinking, and how to work alongside rapidly changing technology.
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