Is computer science still worth studying now that AI can code?

Yes, for the right student. But it has stopped being the default safe bet it was sold as for most of the last decade, and that changes who should pick it.

If you like taking a messy problem apart, building something, watching it break and working out why, computer science is still one of the most useful degrees you can earn. If you were choosing it mainly because every adult around you said it guaranteed a job, this is a good year to question that.

You can feel the worry everywhere at the moment. A Hacker News thread this month carried the blunt title "Computer Science Programs Lose Students as AI Replaces Jobs". Another, about a Princeton PhD who sent 2,300 job applications without an offer, drew close to a hundred replies. Parents forward these headlines to their children. Students forward them to each other. So it is worth slowing down and looking at what is actually happening.

Are students really leaving computer science?

They are, at least in the United States, where the data is best. Undergraduate enrolment in computer and information sciences at four-year colleges fell 8.4% in spring 2026 compared with a year earlier, according to the National Student Clearinghouse Research Center, as reported by Fortune. Graduate enrolment in the field dropped 14% in fall 2025. It is the first sustained fall in about twenty years.

What the numbers can't tell you is why. It is tempting to blame AI for all of it, and the researchers are careful not to. Visa delays have cut international enrolment. Data science now pulls students away as its own major. Weak maths preparation after the pandemic years plays a part too. AI anxiety is one ingredient, not the whole recipe.

Will AI replace software developers?

It is replacing a slice of the work, mostly the slice junior developers used to cut their teeth on. Coding assistants are genuinely good at boilerplate, small functions and tests. That is exactly what a new graduate spent their first two years doing, which is why the entry-level market feels so tight right now.

The harder parts haven't gone anywhere. Someone still has to work out what should be built, untangle a vague request from a real customer, judge whether the generated code is right, and own the result when it isn't. Those abilities come from understanding how computers and systems really work. That is what a good degree teaches, and what a crash course in typing code often skips.

So the people at risk are not "programmers" as a category. They are the people who learned syntax without learning to think in systems.

Is falling enrolment bad news for me?

Possibly the opposite. When fewer people enter a field, the competition for the jobs that remain tends to ease a few years later. Someone graduating in 2030 will be up against a smaller group than the class of 2026 faced. Careers rarely move in straight lines, and the students who pick a subject while it is unfashionable often end up in demand.

There is a catch. That advantage only goes to graduates with real depth: a degree, a handful of things they have built that actually work, and comfort using AI tools as part of the job. A degree on its own is a weaker position than it was five years ago.

What are students choosing instead?

Mostly neighbouring fields rather than a clean exit from technology. Data science and analytics are growing. Universities are adding AI courses across every subject; the University of Florida alone runs more than 200. Some students are moving toward healthcare, engineering and the skilled trades, where AI tends to make people faster rather than replace them.

I'd be careful with that last move, though. Switching away from computer science toward "whatever AI can't do" is the same mistake as picking computer science because it was safe. Both decisions are bets on a job market forecast. Nobody in 2016 predicted the job market of 2026, and nobody today knows what 2036 looks like.

How do I know if computer science is right for me?

Be honest with yourself about three things.

First, whether you enjoy the work itself. Have you ever built anything, even a small script, a game mod or a spreadsheet that does a boring task for you, and found the frustrating middle part strangely satisfying? That feeling is the job.

Second, what kind of problem pulls you in. Some people love abstract puzzles. Others want to help people, or care about how things look and feel. Computer science rewards the first group directly, and pairs well with the others through health tech, design or education.

Third, why you are choosing it. If the main reason is "it pays well" or "everyone says it's safe", you are borrowing somebody else's prediction about the future.

A student who is genuinely curious about how systems work will do fine in computer science whatever the enrolment chart does. A student who isn't will struggle in it even during a boom.

What should I do this year?

Try it before you commit to it. A free introductory course or one small project will tell you more than any article, including this one.

Learn to work with AI coding tools rather than around them, because employers now assume you can. Look sideways too: cybersecurity, computer engineering, data science, and combinations like computer science with biology, economics or design are all strong routes.

And before you lock in a major, find out where your interests actually point.

Where do your interests point?

The most reliable way to choose a field is to start with who you are, not with this year's job forecast. Stride Ahead's Career Interest Inventory maps your interests to the kinds of work that fit them, and shows careers in technology and well beyond it that match. It is free in your Stride Ahead dashboard, and your results stay there so you can compare them as your plans change.