The Washington Post recently published an article saying that, for the first time in 20 years, enrollment in computer science college majors is down. For the last two decades, that major has been one of the most popular at any school.
The decline is significant, but it’s not really a surprise. Students are understandably worried about negative news. The headlines are saying AI is replacing all the entry-level jobs, and the news is full of big tech’s massive layoffs. If you’re a student considering an IT-related career, it would be easy to look at that picture and wonder whether you’re walking into the right room at the wrong time.
The fear is understandable. However, there’s a lot more behind the headlines. Let’s look at what the data says. According to CompTIA’s recent analysis, new tech job postings recently hit a three-year high, and roughly 20% of those active tech job postings are still aimed at candidates with zero to three years of experience.
The opportunities haven’t evaporated. What has changed is what employers expect when you walk through the door.
AI Is Changing Job Requirements More Than Job Availability
The layoffs happening at large tech companies are real, but the story behind them is more complicated than the headlines suggest. Many of the organizations that reduced headcount in favor of AI-driven automation are now quietly rehiring for the same or similar roles because they discovered something important: AI needs oversight. It needs people who understand how it works, where it fails, and how to use it effectively in a real workflow. You can’t automate your way out of needing human judgment.
What this means for entry-level candidates is that AI is not the competition. It’s the curriculum. The candidates who understand the fundamentals of how AI systems function, not just how to use the tools, are who employers are increasingly looking to hire. That distinction is very important in our seemingly AI-driven world.
What Employers Mean When They Say They Want “AI-Literate” Candidates
A few years ago, familiarity with AI tools was a nice-to-have on a resume. Today, it’s closer to a baseline expectation in many IT roles. The gap between candidates who have it and candidates who do not is widening quickly.
AI literacy doesn’t necessarily mean knowing every platform or passing a specific certification. It means understanding the underlying concepts well enough to apply them intelligently, to recognize when a tool is producing unreliable output, and to make judgment calls that a model can’t make on its own. That kind of foundational understanding is what separates a candidate who can use AI from one who can think alongside the tech. Employers know the difference.
The Difference Between Knowing IT and Being Able to Prove It
Technical knowledge matters. Demonstrated technical knowledge matters more.
Hiring managers in IT aren’t making decisions based on transcripts. They’re looking for evidence that a candidate can do the work. Lab environments, home projects, certification exam scores, and real-world problem-solving scenarios all tell a more compelling story than coursework alone. The candidates who stand out in today’s entry-level market are the ones who have the skills and can show their work, not just describe it.
This is one reason hands-on training programs have become increasingly valuable. An employer reviewing two candidates with similar backgrounds will consistently favor the one who can walk through a real scenario, explain their reasoning, and demonstrate that they have actually built or broken something in a lab environment. So yes, make sure your digital portfolio is up to date and impressive.
Four Things That Will Make You a Stronger Entry-Level IT Candidate
If you’re working toward an entry-level IT role, here are a few things worth prioritizing:
- Build foundational knowledge, not just tool familiarity. Understand how the systems and technologies work underneath the surface. That foundation allows you to adapt as the tools change. Skills matter!
- Get hands-on time in real environments. Labs, home networks, virtual machines, and practice exams all count. Demonstrate that you can execute, not just explain.
- Develop your AI literacy intentionally. Learn what AI can and can’t do in an IT context, where it adds value, and where human oversight is essential.
- Stay curious. The candidates employers most want to hire are the ones who are still learning after they get the job. Demonstrating that mindset during the hiring process is an advantage.
The IT job market in 2026 isn’t the same one that existed five years ago. But it’s also not as bleak as the headlines say. The opportunity is real for candidates who are willing to meet the moment with the right preparation.