Welcome to Eye on AI! In this edition...
entry-level job loss due to AI breeds uncertainty…OpenAI acquires Statsig for $1.1 billion – and one of its top executives changes roles…French AI startup Mistral is reportedly finalizing new funding round at $14 billion valuation…is Amazon getting into the AI agent game?Life has always been uncertain, but for generations, young college grads could count on one thing: an entry-level job. It wasn’t glamorous—maybe you fetched coffee, made photocopies, or slogged through low-level tasks for little pay—but it gave you a foothold, the first rung of whatever ladder you hoped to climb.
Now there are signs that, in some industries, that “sure thing” is slipping away. A new paper from
Stanford University’s Digital Economy Lab drew wide attention last week: it found that since late 2022, early-career workers aged 22 to 25 in jobs most exposed to AI automation—like software development and customer service—have seen steep relative declines in employment. The researchers tested other possible explanations, from pandemic-related education setbacks to economy-wide factors like rising interest rates, but concluded that the rise of generative AI was the most likely driver, while noting more data is needed to prove a direct causal link.
There is also a new
Harvard study which also found that the release of ChatGPT in November 2022 marked a turning point in the labor market From 2015 through mid-2022, hiring was on the rise for both junior and senior roles. But beginning in 2022, entry-level employment stalled and then slipped into decline. According to the study, headcount for early-career roles at AI-adopting firms has fallen 7.7% over six quarters since early 2023. The study also found that senior staff, were largely spared. Employment for more experienced workers has continued its steady climb since 2015, avoiding the downturn hitting their younger colleagues.
A
third study, carried out by economists at the Federal Reserve Bank of St. Louis, did not look at whether younger and older workers were affected differently, but it did examine the link between occupations that had adopted AI most intensively and job losses and found a distinct correlation. The impacts were greatest in occupations that used mathematics and computing intensively, such as software development, and much less in blue collar work and fields such as healthcare that were less prone to being automated with AI.
As my colleague Jeremy Kahn
said in Tuesday’s Eye on AI, none of these studies disentangle the effects of AI from the possible effects of the unwinding of the tech hiring boom that took place during the COVID-19 pandemic. During the pandemic, he explained, “many large companies bulked up their software development and IT departments. Major tech firms such as Google,
Meta, and
Microsoft hired tens of thousands of new employees, sometimes hiring people before there was even any work for them to do just in order to prevent rivals from snapping up the same coders. Then, when the pandemic ended and it was clear that some ideas, such as Meta’s pivot to the metaverse, were not going to pan out, these same companies laid off tens of thousands of workers.”
Whatever the reasons, the prospect of post-college unemployment is an uncomfortable place to be—especially for students who thought they could count on steady pipelines into fields like IT or consulting. PwC, for instance, says it plans to recruit a third fewer grads by 2028. Uncertainty, in turn, tends to spread, breeding anxiety—which explains surveys like a
recent one that found that 60% said they felt pessimistic about their career prospects.
Some may tell young people to pivot, persist, or simply pray. But we can’t afford complacency. Society will need these workers one way or another, and that means building real pathways into today’s jobs—and tomorrow’s. What’s happening on the ground to guarantee young people are both prepared for—and included in—the future of work? Opportunity has to exist, even in the face of uncertainty.
Note: Today I published a new deep-dive story on Anthropic’s unusual Frontier Red Team — the group tasked with probing the limits of its top Claude AI models while also shaping how policymakers understand AI’s risks and potential. For this piece, I spoke with Anthropic co-founder and head of policy Jack Clark, had breakfast in Las Vegas with team leader Logan Graham and researcher Keane Lucas, and dug into how this hybrid of security and policy is redefining what “red-teaming” means in AI (and how it could be good for Anthropic’s business). With that, here’s the rest of the AI news.
Sharon Goldmansharon.goldman@fortune.com@sharongoldman
