Education in an AI world (Photo by Christopher Furlong/Getty Images)
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Two years ago, I sat in a guidance counselor’s office with my daughter preparing for her first year of university. The advisor emphasized that the only degree that guarantees a job after graduation is computer science. Now, just halfway through her education, that advice is the opposite of true.
The rules are changing in real time. Parents, universities and employers are all grappling with the same question: what does a meaningful education actually look like in an AI world?
This uncertainty is not a reason to skip university but rather a reason to rethink what it should do to prepare students entering an AI economy. The schools getting this right aren’t the ones rushing to add AI degree programs. They are the ones that were already built for complexity.
What the Data Is Telling Us
Entry-level software development and computational jobs are among the first to disappear. AI was cited as the reason for more than 21,000 U.S. job cuts in April 2026 alone. Anthropic CEO Dario Amodei has warned that AI could eliminate up to half of all entry-level white-collar jobs within five years.
The economics behind that prediction are straightforward. As Nobel Prize-winning AI pioneer Geoffrey Hinton put it: “The obvious way to make money out of AI is to replace workers with something cheaper.” The World Economic Forum projects that 39% of core job skills will change by 2030. Universities have little time to catch up.
This Has Happened Before
In the 1950s, NASA employed teams of mathematicians whose job title was literally “computer” because that is what they did. Katherine Johnson, whose story is told in Hidden Figures, personally calculated the trajectory for John Glenn’s orbit of the Earth in 1962. By the 1970s the electronic computer had dissolved the role entirely.
Dorothy Vaughan, who supervised the computing pool, taught herself computer programming and trained her entire team. A similar story is shaping up now, but across far more occupations and at far greater speed.
What Holds Up
AI thrives on repeatable tasks that are often the very training ground for young hires. In a world where AI can outperform on so many of those tasks, employers increasingly need critical thinkers, good communicators and people who can work across company departments. These once called “soft” skills are far more difficult for AI to replicate. Companies that want to use AI to its fullest need them, or risk AI driving straight highways when the world is full of twists and turns.
JPMorgan Chase CEO Jamie Dimon put it plainly: “My advice to people would be critical thinking, learn how to be good in a meeting, how to communicate, how to write. You’ll have plenty of jobs.” The World Economic Forum data backs that up, with resilience, curiosity and creative thinking rising faster in employer priorities than technical credentials.
Three Schools Worth Watching
The number of U.S. institutions offering AI degrees has nearly doubled since 2022. But chasing AI programs may be solving yesterday’s problem. The deeper issue is the silos that are the hallmark of much of higher education, structured to produce specialists in a single domain at a time when the world is demanding the opposite. While many educational institutions work to adapt, there are existing models that provide guidance as to what good looks like.
One approach makes the workplace part of the curriculum. Northeastern University builds its undergraduate program around co-op, where students alternate full semesters of coursework with full semesters of paid, full-time work across multiple employers and industries. Students hold real jobs in multiple environments before collecting a diploma and increasingly, that means working alongside AI tools as they evolve in workplaces. As President Joseph Aoun has said: “Knowledge is becoming a commodity. Experience is not.”
Some schools embed experiential, hands-on learning directly into the institution’s architecture. College of the Atlantic in Bar Harbor, Maine offers exactly one major, human ecology. Students design their own course of study across disciplines from the ground up. COA never built departmental silos into its model. Students work on real projects with real stakes: ecological research, community policy, sustainable design. The education centers on doing, not just learning about doing. As President Lynn Boulger explains: “Our curriculum requires students to hold complexity without reducing it. COA was built for this.”
Other schools dismantled the structure that creates silos in the first place. In 2002, Arizona State University President Michael Crow dismantled 85 traditional departments and rebuilt the university around 35 transdisciplinary units including a School for Complex Adaptive Systems and a College of Global Futures. Crow calls AI “the great equalizer.” OpenAI partnered with ASU in 2024, activating more than 500 projects across disciplines. ASU pivoted long before AI became a pressure point and now finds itself well positioned for its graduates.
University is not the only path worth considering. The skilled trades, long undervalued, are among the most resilient to AI disruption. Electricians, plumbers and carpenters are in demand at a scale the AI infrastructure boom has made urgent.
But for those who do choose university, the question worth asking isn’t which major AI won’t touch. It’s what kind of person an education should produce: someone who can think across domains, sit with complexity, adapt when the ground shifts and lead the tools rather than follow them.
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The author previously taught at College Of The Atlantic and has no current affiliation with the institution.