College students are trying to figure out how to incorporate AI 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 the job market he had been preparing for was changing in real time.
After applying to more than 3,000 jobs and internships over his time in school, the 23-year-old began noticing employers were no longer asking only for traditional computer science skills. “I saw the job descriptions evolve from asking for computer science fundamentals to being able to use AI tools, and then build with AI tools,” he says. “Halfway through my master’s degree, I realized that I also needed to add this layer to my current portfolio.”
Students across the country are making similarly evolving calculations as artificial intelligence reshapes how they think about majors, careers and the value of college itself. A new Lumina Foundation-Gallup survey of more than 3,500 students pursuing bachelor’s or associate degrees found that 47% had considered changing majors because of AI, either “a great deal” or a “fair amount.” The most likely to have considered it were those in tech fields, with 70% having given it that level of thought. The least likely to ponder a change? Students studying the natural sciences and training for the health care professions, which not so coincidentally have been the fastest growing employment fields recently.
“Students are not waiting for the future of work to arrive,” says Courtney Brown, vice president of impact and planning at Lumina Foundation and the study’s lead researcher. “They’re trying to respond to it now and figure out what’s best.”
That’s 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 understandably trying to identify which career fields might survive AI disruption. (A recent Stanford University study found employment falling among younger workers in occupations highly exposed to generative AI.)
But Brown warns students may be overestimating their ability to “future-proof” a degree. “I don’t think there’s a winning lane,” Brown says, comparing the student dilemma to trying to choose the fastest-moving line at a grocery store. “All lanes are going to lead to AI, which is going to impact every single major. It’s just a difference of timing.”
Instead, Brown says students should think instead about how AI may change work across professions.
2. Look for Majors Combining Human Skills and Technical Ones
Students increasingly need programs that blend technical fluency with what employers still struggle to automate. Even students immersed in AI worry about overreliance on the technology. “As humans, we are always wired to find the easiest way across the problem,” Mister says.
“The important thing is to look for majors that combine technical skills with distinctly human capabilities, like communication, creativity and problem solving,” says Brown. (Some examples she gives: business analytics, industrial engineering, public health, architecture, environmental studies, cognitive science and digital media or game design.)
Brown says those “durable” human skills are often taught in higher education but poorly explained in terms of career relevance: “Until you’re about to graduate and you’re looking for a job, nobody helps you communicate or translate [these skills] into the world of work.”
At the same time, Brown says she is watching students increasingly pair humanities and social sciences majors with digital and AI-related disciplines, rather than abandoning humanities entirely. There’s evidence that in the past, at least, college grads with majors in two disparate fields have been substantially less likely to suffer career shocks such as long periods of unemployment.
3. Pay Attention to Whether Colleges Are Actually Teaching AI Literacy
While AI cheating in college has gotten a lot of attention, Brown says universities are increasingly concerned about a different malaise: AI dependency. “The challenge for institutions is finding the balance between protecting foundational learning while also preparing students to work effectively with AI,” she says.
Many universities still lack clear guidelines, and more than half of the participants in the Lumina and Gallup survey said at least some of their classes lacked clear AI rules.
Brown argues colleges should help students understand responsible use, deepfakes, ethical concerns and how AI should “supplement and not take over what humans should be doing.”
Mister saw that 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 need to understand what the code is doing, and you need to know the concept behind it.”
As a TA, he assessed students through in-person interviews where they had to explain the concepts behind their projects.
4. Look for Colleges that Integrate Career Guidance Earlier
Many students receive little meaningful career guidance until they are close to graduation. “The career services office shouldn’t be where you visit your last week before graduation,” Brown says.
Instead, she suggests, career advising should begin from day one and help students understand how what they are learning connects to evolving workforce demands. “Career guidance has to evolve faster than it’s evolving,” she says.
That may matter even more as families increasingly question college’s return on investment. (It’s not just career advising, that matters. It’s worth considering schools that promote internships and work experiences, too.)
5. Don’t Mistake AI Avoidance for AI Preparedness
If colleges treat AI as a tool to be avoided, they may put students at a disadvantage.
“We’re doing a disservice if we try to put it in a box and say AI is over here and don’t use it, when it’s a reality that we’re all experiencing, and it will be the reality of the workforce,” Brown says.
She acknowledges many institutions are struggling to keep up with the pace of change. But colleges that fail to adapt quickly enough risk falling behind students who are already trying to navigate an AI-driven economy on their own.
“The institutions that are not nimble, that aren’t able to move quickly enough, are the ones going to be left behind,” she says.
In the AI era, students may be better served 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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