Top College Degrees That Lead to High-Paying AI Careers

The college major you choose today could determine whether you thrive in—or get left behind by—the AI economy. Since ChatGPT launched in 2022, the biggest wage gains have gone to workers in AI-exposed jobs, according to a Stanford University and World Bank study. Those building and guiding AI systems are landing some of the economy's fastest-growing roles, with median salaries topping $135,000.

“Math and computer science skills are always helpful,” said Eugene Vinitsky, a professor and AI researcher at New York University's Tandon School of Engineering. “But in the future, a powerful combination will be understanding AI deeply enough to avoid basic mistakes—while also having real expertise in another domain.”

Don't expect to find a single AI degree that meets all your needs. Instead, experts suggest building technical fluency in AI while also focusing on the field of your choice—whether that's robotics, design, economics, or philosophy. (By the way, want to talk like an insider? Pros often refer to non-AI fields as domains.)

Best Degrees If You're Looking to Land a Job in AI

Everyone from high school students and their parents to those considering a mid-career shift have found themselves up to their eyeballs in ads for new AI majors and certificate programs. The chart below simplifies that landscape, showing which degrees are asked for by employers in job ads and are emerging gateways into the field.

Each row in the table above represents a different path that can lead to an AI-related career. Some, like computer science or data science, are obvious. Others—such as cognitive science, linguistics, design, or philosophy—show how deeply interdisciplinary AI is.

What matters most isn’t the title of your degree, Vinitsky said, but the mix of skills it builds: math and coding for understanding the technology, plus knowledge of a field that interests you so you can apply that knowledge to real-world problems.

Look closely and you’ll notice that almost every successful path is built on top of a broad foundation, consisting of such things as:

• Solid schooling in math, statistics, and computer programming
• Hands-on experience via internships or research
• Curiosity about how technology affects people and society
  

Related Stories

Facing Job Market Struggles, College Majors Seek New Paths to Success

The Fastest Growing Industries for Graduates

The Skills You'll Need—And Many Forget

Many universities are teaching AI theory but neglecting the messy, unglamorous skills that actually get you hired.

"The biggest missing thing is professional software development skills and research organization. It really is more of a bottleneck in reality than you think," Vinitsky said. Translation: You might ace machine learning (ML) courses but fail to land interviews because you can't write production-quality code or organize complex projects.

How can you make sure that doesn't happen to you?

"I'm a big believer in supplementing every degree with a strong [computer science] background," Vinitsky said.

Here are concrete tips for making the most of your burgeoning opportunity in AI:

• Choose depth over buzzwords: Don't chase the latest, hottest course titles. "Applied generative AI" sounds exciting, but you'll get further by first mastering core math, probability, and programming.
• Hands-on experience matters more than your GPA: Real-world practice gives you industry contacts and resume-worthy experience. So, aim for internships and work on open-source projects as well as undergraduate research projects.
• Learn how to learn: Because AI changes constantly—in many ways, it's a very new field—your long-term edge is adaptability. Students who understand how to teach themselves new tools and to think critically will likely stay more employable.
• You're working with AI, but you're not the robot: The next decade of AI jobs is likely to involve design, communication, and policy as much as technical work. If you can explain a model's decision, translate between engineers and executives, or see ethical risks early, you'll add value that can't easily be automated.
• Be skeptical of the instant-AI degrees: Look for evidence of student outcomes, such as internships, research funding, and graduate placement. Vinitsky's advice: "Think about student outcomes related to jobs. Are people winding up at places you'd be excited about?" Don't just look at marketing materials—see if the courses are well organized and if you can find where graduates landed.

Below are notable programs in AI that can help you with all of the above. Bear in mind, these are leading examples, not an exhaustive list of the many programs that might be better for you.

How We Identified the Majors and Programs Above

To give readers a clearer picture of which college programs actually prepare students for careers in AI, we drew on academic rankings, program documents, faculty research, and real-world hiring data. The Notable Programs column in the chart above combines information from the QS World University Rankings by Subject (data science and AI), Times Higher Education's computer science rankings, U.S. News & World Report's undergraduate AI programs, and research-focused sources like CSRankings and EduRank. To test how well those programs align with today's job market, we reviewed several hundred recent AI-related job postings on LinkedIn and Indeed, focusing on entry-level and early-career roles.