Is AI Really Behind the Entry-Level Tech Slump? What the Evidence Supports and What It Doesn't

October 3, 2026 analysis AI entry-level

Companies increasingly cite AI when they cut staff, and headlines about struggling computer science graduates usually do the same. But “AI was mentioned” and “AI caused it” are different claims. Here is what the sources support.

Evidence that points to AI

• More cuts are attributed to AI. Challenger data cited by Computerworld shows AI blamed for 40% of tech job cuts in May, up from 7% in January.
• Employers are shifting code work to AI. The AP reports that Microsoft, Meta and Google are using AI for a larger share of code writing.
• Some cuts are genuinely driven by AI adoption. The SkillSyncer tracker says this applies to many layoffs at the biggest companies.

Evidence that points elsewhere

• The slowdown started earlier. An On EdTech analysis, published as sponsored content on Higher Ed Dive, argues that the downturn in new-graduate hiring began before generative AI was widely adopted, and that AI may be speeding it up without being the main driver. Because it is sponsored content, weigh it accordingly.
• Too many graduates for the openings. The AP says the elevated jobless rate partly reflects the large number of students who enrolled during the coding boom.
• A pandemic hangover. Futurism describes companies embracing AI tools while cutting entry-level roles and pulling back from COVID-era over-hiring.
• Blame can be convenient. SkillSyncer acknowledges that some companies attribute to AI cuts they would have made regardless.

What is still unclear

IEEE Spectrum notes that entry-level hiring at the largest tech firms fell sharply, yet it remains unclear whether those cuts are actually a result of AI. Counting methods also blur the picture, since many trackers tag a layoff as AI-related whenever the company or press says so, even if the money was simply redirected to AI projects.

A fair reading

The honest summary is that several forces are overlapping: a glut of graduates, post-pandemic correction, higher interest rates, spending moved toward AI, and some real automation of coding work. Anyone claiming a single cause is going beyond the evidence. For a student, the useful conclusion is the same either way: the entry-level market is tougher, and the skills employers ask for are changing.

My take

Whatever the exact mix of causes, I think software engineering is still worth studying, but we need to stop seeing it as just coding. My view is that new grads need strong fundamentals, especially data structures and algorithms, because without them you can’t tell an AI tool in enough detail what you want built. System design matters just as much, since someone still has to decide how the pieces fit together. I’m not a senior engineer, so this is what I’ve seen and believe, not settled fact.