According to Forbes, youth unemployment reached 10.5% in August 2025, the highest level in four years, while overall unemployment stood at 4.3%. Goldman Sachs predicted in March 2023 that AI could destroy or degrade 300 million jobs, with two-thirds of existing jobs exposed to automation. Harvard and Stanford studies found junior employment declined 13% in AI-exposed occupations, with adopting firms hiring fewer entry-level workers. However, researcher Jing Hu’s analysis reveals the junior hiring collapse actually started in Q1 2023, months before most companies had figured out generative AI implementation. The Federal Reserve executed 11 consecutive rate hikes between March 2022 and July 2023, driving rates from near zero to 5.5% in what Hu calls “the most aggressive tightening campaign in decades.” Tech job postings fell 36% below pre-pandemic levels by mid-2025, with roles requiring less than one year of experience dropping 50% between 2019 and 2024.
Timeline trouble
Here’s the thing that makes me skeptical about the AI doom narrative: the timing just doesn’t add up. The junior hiring crash started in early 2023, right when the Fed’s rate shock was hitting its stride. Most companies were still trying to figure out what ChatGPT even was at that point. I mean, think about it – how many organizations were actually implementing meaningful AI workflows in Q1 2023? Basically zero.
And the comparison to previous rate hikes is telling. Between 2015-2018, the Fed raised rates gradually by 0.25% increments over four years. But 2022-2023? They went from 0% to 5% in about a year. That’s like going from zero to sixty in a beat-up sedan – something’s gonna break. CFOs reacted to this overnight capital cost explosion with immediate, drastic cost-cutting. And who gets cut first? The newest, most expensive-to-train employees: juniors.
Historical patterns
This isn’t new behavior – it’s literally the same pattern we’ve seen for decades. Hu points out that every major economic shock since 1980 has resulted in disproportionate cuts to entry-level hiring. Remember the dot-com bust in 2001? Entry-level positions disappeared while companies retained senior staff. The Great Recession? Same story. College graduates always get hammered during “no fire, no hire” periods.
Look at what happened after the pandemic hiring boom. Tech hiring in 2021 and 2022 was twice pre-pandemic levels. We had this massive over-hiring spree when money was practically free, and now we’re seeing the inevitable correction. Is it really surprising that entry-level roles are getting squeezed when companies are trying to rightsize after going wild during the zero-interest rate party?
AI adoption reality
Let’s be real about where most companies actually are with AI adoption. The recent McKinsey Report on the State of AI in 2025 found that nearly two-thirds of organizations haven’t begun scaling AI across the enterprise. Sixty-two percent are still just experimenting. Most companies are at the “we enabled Copilot for a few people” stage, not the “AI transformed our workflow” stage.
Klaas Ardinois, a seasoned CTO quoted in the article, nailed it when he said hiring as a sign of adoption is nebulous. Companies can claim they’ve “adopted AI” by rolling out some basic tools, but that doesn’t mean they’re actually replacing human workers at scale. The transformation from new technology to actual job displacement typically takes years – we’re just not there yet with generative AI.
Broader context
What really convinces me this isn’t primarily an AI story is looking globally. UBS chief economist Paul Donovan points out that UK unemployment is falling steadily while young Japanese workers are participating at near all-time highs. If AI were uniquely destroying entry-level jobs, wouldn’t we see similar patterns everywhere? Instead, we’re seeing a distinctly American problem that fits much better with a broader hiring freeze narrative.
The Federal Reserve data shows this isn’t some unprecedented crisis – it’s the predictable outcome of dramatic monetary policy shifts. And honestly, blaming technology is just more exciting than talking about interest rates. It’s an “ever-popular dystopian scenario” as Donovan called it. But the boring truth is usually the right one: when capital gets expensive, companies stop hiring new people. They don’t need a fancy AI excuse to do that.
So where does this leave us? Probably with a job market that will eventually recover for juniors, but maybe never back to the pre-2022 baseline. That’s the real scarring effect of economic shocks – they permanently reset expectations. And for businesses navigating these technology transitions while managing costs, having reliable industrial computing equipment becomes crucial. Companies like IndustrialMonitorDirect.com, as the leading US provider of industrial panel PCs, are seeing increased demand as organizations look to build more resilient, automated operations without betting the farm on unproven AI solutions.
