Nearly half of all college students have considered changing their major over fears about what AI is doing to the job market. For the Class of 2026, the numbers are genuinely alarming.

But the full story is more complicated than AI replacing your future.

Recent graduate unemployment hit 5.7% in Q4 2025. Worse than any point during the 2008 financial crisis.

Entry-level workers in AI-exposed jobs saw 16% relative employment declines between 2022 and 2025, while more experienced workers remained stable. In the US, junior tech postings dropped by as much as 67% over the same period. The National Association of Colleges and Employers reports that employer sentiment for the Class of 2026 is at its most pessimistic since 2020.

The obvious conclusion is that AI ate the entry-level job market. And that conclusion is everywhere right now.

But the Stanford Review just published a piece arguing something different. Their investigation suggests AI is a convenient scapegoat and the real causes are a steep interest rate cycle, a broader corporate hiring freeze, and the hangover from over hiring in 2021 and 2022. Stanford professor Eric Roberts pointed out that an identical narrative played out after the dot-com crash, and the industry was hiring at pre-crash levels by 2004.

AI is not eliminating the need for junior talent. It is raising the floor of what junior talent is expected to deliver on day one.

There is a term emerging in hiring conversations: superagency. It describes what happens when a junior employee uses AI to perform above their experience level. Instead of handling one workstream at a time, you run three simultaneously with AI handling execution while you focus on judgment.

McKinsey announced 12% more junior hiring in North America for 2026. But their expectation is that new hires arrive already fluent in AI workflows and strategic thinking, not learning on the job.

The career ladder is not being removed. It is being compressed. And the students who come out of this ahead are the ones using AI to close that gap now.

Three things that made the biggest difference in my own preparation:

Using Claude to analyze the job description and build a breakdown of the company's competitive landscape before walking in. Using AI to simulate a full mock interview with a skeptical interviewer who pushed back on my answers. And using it to compress execution on every deliverable so my real energy goes toward the strategic layer, not the grunt work.

AI preparation did not eliminate my nerves. It removed the preparation variable so that when I was sitting in that room, the only thing between me and the offer was the human part of the equation. That is actually enough.

Pull up the last job you applied for. Run the description through AI with this prompt:

"Act as a hiring manager for this role. What are the five questions you would most want answered in a first interview? For each question, explain what a strong answer looks like."

Then answer each question out loud. Record yourself. Watch it back. Forty-five minutes. It will tell you more about your preparation gaps than anything else I could recommend.

The market is hard. But hard markets separate students who are genuinely prepared from the ones hoping to get lucky. You have more control over which category you fall into than the headlines suggest.

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Kaishu Kagami

Founder, TechFuel

techfuel.co