Employers aren’t giving up on computer science grads. Here’s what they want instead

Not long ago, a computer science degree was widely seen as a golden ticket to a lucrative career. Over the past year, a different narrative has taken hold: In the age of artificial intelligence, that path is collapsing. From coders working at Chipotle to the ”bursting” of the computer science bubble, a growing chorus has suggested that a degree once synonymous with opportunity no longer delivers.

The numbers don’t match the story. The pessimistic narrative around computer science (CS) hinges on two main arguments: that CS graduates have recently faced elevated unemployment, and that too many have been unable to secure a good first job. Each of these points is true on the surface. But they are also overstated—and they misread the transformative impact that artificial intelligence is already having on the economy.

Lower underemployment

After the launch of ChatGPT, recent CS graduates did experience unemployment a couple of points higher than the average for other recent grads. But they continue to experience substantially lower underemployment than most of their peers, a critical distinction, because it means they are more likely to land professional, college-level roles that make meaningful use of their degree, including a variety of well-paying roles across the tech sector and beyond.

Nor has AI eliminated employer demand for CS talent. In a recent national survey conducted by Strada, an IT services and consulting firm, employers rated math-intensive STEM graduates, including those with CS degrees, as the most difficult to attract for entry-level positions and the highest for critical thinking across all fields. Research from the National Association of Colleges and Employers confirms the point: Computer science still tops the list of highest projected salaries for new graduates and ranks third in overall employer demand. These aren’t the statistics of a field in free fall.

Looking ahead

But the data on where computer science graduates stand today tells only half the story. The more important question—the one that students, parents, and university leaders should be asking—is where they will stand five years from now. And on that front, there is reason for both optimism and urgency.

The rise of AI has not eliminated the need for people who can build and direct technology. Instead, as AI becomes both more sophisticated and more available, we’re seeing a version of the Jevons paradox at work: When a capability becomes cheaper and more efficient to use, demand for that capability can greatly expand. A growing number of technology leaders are pointing to the need for forward-deployed engineers who can sit inside an organization, apply AI tools to a specific business problem, and rebuild the workflow around the results. The computer science jobs of tomorrow will rely not on fluency with tools and models that are easily commoditized, but on the ability to leverage AI to rewire how an organization runs. Demand for people who can do that is only going to grow, and the talent pipeline to fill that demand does not yet exist.

This is the labor market story that the obituaries for computer science are missing. Multibillion-dollar bets across private equity and venture capital are being made on exactly this premise—that the next wave of value creation will be built by people who know how to direct AI effectively. Computer science graduates remain among the best positioned to be those people.

That’s not to say that the colleges and universities producing our country’s CS graduates should rest on their laurels. The real gap in the labor market right now is the disconnect between what schools are graduating and what employers can actually evaluate. Rather than transcripts, businesses increasingly want evidence that a student can apply skills in a real environment. That means hands-on and experiential programs—internships, apprenticeships, applied AI projects—that let students practice and demonstrate the capabilities the market is asking for.

Some institutions are moving fast. The City University of New York recently fast-tracked new AI fluency requirements. Howard University is expanding AI coursework across its campus this fall. These schools aren’t waiting for demand to recover, because among employers who understand where the technology is headed, the demand never left.

Fixing the disconnect

To strengthen job prospects for graduates, colleges and universities should work on ensuring that their computer science programs better connect with the needs of industry. That means teaching AI with an eye toward the applied skills employers are seeking. It should include more hands-on and experiential programs, like internships and tech apprenticeships, that help students practice the skills they’ll need in the workplace—along with AI-enabled simulations that bring more real-world work environments into the classroom.

Employers have a role to play, too, by partnering with colleges to expand those opportunities and make clear which skills matter most on the job. Colleges can also increase support for in-demand industry certifications that employers often look for in entry-level candidates. They might even encourage more students, across degree fields, to minor in computer science. Forward-deployed engineers are already being hired, and they are just one example of how AI is reshaping the labor market. Colleges, universities, and employers will need to work together to help students prepare for what comes next.

A doom-and-gloom perspective on computer science is a misreading of both the current data and the trajectory of the field. Computer science remains one of the most reliable pathways to economic security and mobility, and it sits at the center of one of the most consequential technological shifts of our time. The market for computer science graduates is not collapsing. It’s evolving—and for those prepared to navigate it, the opportunities ahead may be the largest the field has ever seen.

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