The belly of the snake: Entry-level unemployment and the coming skills gap

Rising entry-level unemployment: A bleak picture

Entry-level unemployment is rising drastically, which is bad news for students or colleges. A recent report from Oxford Economics indicates that the unemployment rate for new college grads has increased by 1.6%, which is close to triple that of the overall rate (0.6%). The New York Federal Reserve paints a similar picture. According to their data, in March 2025, the unemployment rate for new college graduates was 5.8% versus 2.7% for all college grads. In March 2023, the rates were 4.1% and 2.1% respectively. To drive home the gravity of the situation, consider these additional statistics. In 2023, the ratio of new grad unemployment to all college grad unemployment was 1.95. As of March 2025, that ratio was up to 2.14. That might not seem like much, but it is. It’s a 10% increase in just two years. If that trend continues, higher ed, and our students, are in trouble.

The Oxford report attributes the increase in large part to a mismatch in the employment market. The gist of this argument is that there are more graduates than there are entry-level jobs, especially in computer science. Although the current situation is heavily affected by reduced hiring in the tech sector, that will soon change.

One of the first serious applications of generative AI was to make designing and writing computer code more efficient; much more efficient according to many. This led to rapid and dramatic reductions in “head count” in tech. Since governments and other institutions have been pushing STEM (especially technology) programs for many years, there is an increasing number of computer science grads. When more grads meet fewer jobs … well, you get our current situation. Labor supply is exceeding labor demand, resulting in increased unemployment. Today, much of that is concentrated in tech, but that won’t be the case in the future.

As the range of generative AI applications continues to expand, more and more employment sectors will be affected. Accounting, marketing, education, communication and media, even healthcare, all of these will experience some degree of the same phenomenon. In reality, all forms of knowledge work are in jeopardy. Nobody knows the timing, but the effects are coming, barring a zombie apocalypse of course.

This presents obvious challenges for higher education. We need to adapt, and quickly. Unfortunately, we’re not good at adaptation and we certainly don’t do “quick.” Institutional inertia is going to be a significant problem. Although we don’t want to overreact and move reflexively, we do need to adapt much more quickly than we normally do. Frankly, I’m not sure we’re up to it (and I work for a school that moves relatively quickly). Unfortunately, the reduction in hiring of entry-level workers is going to have hidden, downstream effects that may ripple throughout the economy.

The skills gap

Let’s assume that the decline in entry-level jobs is not a blip, but a systemic change, an assumption that is very likely valid. If so, within a few years, organizations are going to find it harder and harder to find more skilled workers and managers. Entry-level jobs have long been the proving ground for higher level workers. If the entry-level pipeline is cut off (or greatly reduced), organizations have a huge problem. Where will they find the higher-level workers? There will be a chasm between skill level of the remaining entry-level workers and their AI replacements and the skill requirements for higher-level positions. In other words, there’s a skills gap.

My guess is that very few people are thinking about this yet, but it’s going to be a HUGE problem. Yes, maybe Company A can poach workers from Company B, but at a macro level that’s just playing musical chairs.

It’s possible that there will be similar reductions among more highly skilled workers, but that just creates a host of other societal problems. At the extreme, cascading reductions in higher and higher-level positions results in nobody being left. That doesn’t seem likely, so there will be a skills gap at some point. Mark my words, in the next ten years or so, this is going to be a major issue.

Solutions?

What can be done to avoid the skills gap? Addressing the problem requires considerable effort from colleges and employers. Colleges need to become more adaptable. We need to be able to change more quickly and effectively. In the world of AI, a curriculum change that takes two years to be approved will be vastly out of date. Yes, we can and should double-down on critical thinking and other similar skills, but that won’t be enough. Although large-language models can’t really think critically, they are getting better and better at simulating critical thinking.

I may be biased, but I think we need to go all in on AI. We need to teach students to use AI in ways that help them learn AND enhance their capabilities, including their critical thinking capabilities. Although this will require massive investments in time, effort, and money, I don’t see any other viable option. The chance that AI is just another over-hyped technology seems very small to me. I’ve said it over and over, we need to help students learn how to use AI ethically AND effectively. Anything less is a disservice to students and society.

Of course, exactly how to do this is an open question, but there are a few clear needs. We need to be willing to experiment and to fail. We need to streamline approval processes. We need to avoid letting edtech companies lead our AI efforts. They’re selling products and services. We’re trying to serve our students. We, educators, need to drive the proverbial bus on AI change. If we do not take up this challenge, changes will be forced on us, likely to the detriment of ourselves, our students, and society.

But, it’s not all on us. Employers need to rethink some things as well. When I graduated back in the late 1970s, the norm was for employers to have carefully thought out management development programs. New hires often rotated through different positions to learn how the organization operated. Training and development programs went along with the experiences, leading to well-trained, experienced managers. Those are largely gone now. Companies, in pursuit of the bottom-line and higher share prices, have vastly reduced investments in their workers. That has to change. Rather than focusing on how AI can reduce headcount, organizations need to be willing to invest in using AI to reach new markets and improve overall operations. Focusing on efficiency over effectiveness is, in the long run, a bad idea.

The necessary changes require shedding deeply entrenched practices and mindsets. Although this makes me skeptical about our ability to adapt quickly enough, one thing is crystal clear to me. Inaction will lead to consequences far worse than most imagine. We must push our leaders to move beyond just embracing AI; we need to make fundamental changes that prepare students for a future where AI is as ubiquitous as the Internet and mobile devices. That future is coming, sooner than we might expect.

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Want to continue this conversation? I'd love to hear your thoughts on how you're using AI in your courses. Drop me a line at Craig@AIGoesToCollege.com. Be sure to check out the AI Goes to College podcast, which I co-host with Dr. Robert E. Crossler. It's available at https://www.aigoestocollege.com/follow.

Looking for practical guidance on AI in higher education? I offer engaging workshops and talks—both remotely and in person—on using AI to enhance learning while preserving academic integrity. Email me to discuss bringing these insights to your institution, or feel free to share my contact information with your professional development team.