Artificial intelligence has changed the conversation around education almost overnight. Tools that write code, debug programs, and explain complex systems in plain language are now available to anyone with an internet connection. For students weighing years of study and a serious financial commitment, the question is fair and pressing: does a computer science degree still hold its value when machines can do so much of the work? The short answer is yes, but the longer answer deserves a closer look. Understanding what a degree actually delivers, and what it costs, matters more now than ever.
What “Worth It” Really Means
Value is not a single number. People often reduce the question of a degree to starting salary, but that misses most of the picture. A computer science education shapes how you think, not just what you can build. It teaches you to break large problems into smaller ones. It trains you to reason about systems, trade-offs, and failure.
Those habits outlast any single programming language or framework. Technology shifts constantly. The thinking behind it changes far more slowly. That gap is exactly where a strong degree earns its keep.
The Job Market Behind the Degree
The numbers remain encouraging, even with AI in the mix. According to the U.S. Bureau of Labor Statistics, computer and information technology occupations reported a median annual wage of $105,990 in May 2024, well above the median for all occupations. Demand is not slowing down either.
Software developer roles are projected to grow 15 percent from 2024 to 2034, a pace the BLS describes as much faster than average. That translates to roughly 129,200 openings each year across the field. Some of those jobs come from growth. Others come from people retiring or moving on. Either way, the pipeline stays busy.
These figures tell a clear story. Companies still need people who understand how software is designed, secured, and maintained. AI has not erased that need. In many cases, it has raised the stakes.
What AI Changes, and What It Doesn’t
It would be dishonest to pretend nothing has shifted. AI tools can now generate working code, write tests, and handle routine tasks that once filled an entry-level workload. This is real, and it affects how junior roles are structured. Some basic coding work is being automated away.
But automation rarely removes a profession. More often, it moves the value somewhere else.
The Skills That Still Need People
When a machine can produce a first draft of code, the human job shifts toward judgment. Someone has to decide whether the output is correct. Someone has to catch the subtle bug the model confidently introduced. Someone has to weigh security, cost, and long-term maintenance against a tight deadline.
These are not coding tasks in the narrow sense. They are engineering decisions. A computer science degree builds the foundation that makes those decisions possible. You cannot review what you do not understand. You cannot guide a tool whose output you cannot evaluate.
AI also raises the ceiling on what small teams can accomplish. That means employers increasingly want people who can direct these tools rather than simply use them. The graduate who understands algorithms, data structures, and system design is positioned to lead that work, not be replaced by it.
More Than Code: The Hidden Value of the Degree
A degree offers things that self-teaching often cannot match. Structure is one. Over several years, a good program walks you through theory, practice, and the connective tissue between them. You learn the why, not just the how.
Then there is the network. Classmates become colleagues. Professors become references. Internships open doors that a portfolio alone might not. Many employers still use the degree as a baseline signal when sorting through hundreds of applicants.
None of this means a degree is the only path into technology. Bootcamps and self-study work for some people. But for those aiming at competitive roles, research positions, or specialized fields, the credential continues to carry real weight.
Paying for the Degree: How Private Student Loans Work
Cost is the part of this decision that keeps many families up at night. Tuition has climbed steadily, and a four-year program represents a major investment. Understanding your funding options is part of making a smart choice.
Most students start with federal aid. Grants, scholarships, and federal loans usually come first because they offer fixed rates and flexible repayment protections. For many people, though, that funding does not cover the full bill. That is where private lending enters the picture.
Private student loans are issued by banks, credit unions, and online lenders rather than the government. Approval and interest rates depend heavily on credit history and income, so many students apply with a cosigner to secure better terms. Rates can be fixed or variable. Some lenders offer specialized products, including private student loans for STEM majors, which are designed around the earning potential and longer study timelines common in technical fields. Before signing anything, it pays to compare the annual percentage rate, the repayment schedule, and any fees across multiple lenders.
A few habits make borrowing safer. Borrow only what you actually need. Read the full terms before you commit. Map out your expected monthly payment against a realistic starting salary in your field. The strong wage data for computer science roles makes this math more manageable than it is in many other careers, but it is still math worth doing carefully.
Weighing the Decision
So how should you think it through? Start with your goals. If you want to work on hard technical problems, build a long career, and keep your options open, the case for a degree stays strong. The field rewards depth, and depth is hard to fake.
Be honest about the costs, both in money and time. A degree only pays off if you finish it and use it. Factor in your learning style, your financial situation, and the kind of work that actually interests you. AI is a tool you will use throughout your career, not a reason to skip the foundation that lets you use it well.
Consider the trajectory, not just the entry point. Entry-level work may shrink in some areas, but mid-career and senior roles continue to demand people who understand systems at a deep level. The degree is an investment in that longer arc.
Conclusion
The age of AI has not made computer science obsolete. If anything, it has clarified what the field is really about. Writing code was never the whole job. Understanding problems, designing solutions, and exercising sound judgment have always been the core, and those skills are exactly what a strong education develops. A computer science degree remains a serious commitment, and it is not the right fit for everyone. But for those drawn to the work and willing to do it thoughtfully, the value is still very much there. The tools will keep changing. The people who understand them will keep mattering.
Photo by Flipsnack: Unsplash
