First-of-its-kind Stanford study says AI is starting to have a ‘significant and disproportionate impact’ on entry-level workers in the U.S.

1) Entry-level workers hit hardest

2) A fading pattern since 2022

3) Automation vs. augmentation

4) Sturdiness

5) Employment, not wages

6) Widespread consistency

Nick Lichtenberg is Fortune Intelligence editor and was formerly Fortune's executive editor of global news.

Stanford University has published a first-of-its-kind study on Tuesday that reveals “the AI revolution” is already beginning to have a “significant and disproportionate impact on entry-level workers in the U.S. labor market,” especially those aged 22-25 in highly AI-exposed professions like software engineering and customer service.

The research, led

The study highlighted six facts that Brynjolfsson’s team believe show early and large-scale evidence that fits the hypothesis of a labor-market earthquake headed for Gen Z.

First, employment disruption is not happening evenly across the workforce. The largest declines are concentrated among young, entry-level workers—those whose skills are most easily replaced

The report says it’s uncovered “substantial” declines in employment, especially for workers aged 22 to 25. This dovetails with mounting evidence from investment banks and surveys of layoff announcements, as Goldman Sachs has calculated a shrinking premium from a college degree, implying that entry-level workers are struggling to differentiate themselves in this hiring climate. Bank of America Global Research, meanwhile, has noted that since 2022, the unemployment rate for recent graduates has started to exceed the overall unemployment rate for the first time in recent memory.

Secondly, the study finds fewer young people are being hired into AI-exposed occupations, with employment growth for young workers stagnant since late 2022—consistent with BofA’s analysis of census data.

In jobs less exposed to AI, the study says, young workers have experienced comparable employment growth to older workers. In contrast, entry-level workers in the occupations most exposed to AI have experienced a 6% decline in employment from late 2022 to July 2025, while older workers have seen 6%-9% growth. The results suggest that the AI revolution is driving “tepid” overall employment growth for workers aged 22 to 25, the study adds.

An important distinction is that not every use case for AI is leading to a decline in employment, the data suggests. The negative impacts are concentrated in fields where AI is more likely to automate tasks rather than augment work, and occupations with mainly augmentative AI applications have not seen similar declines in entry-level hires.

The team says it distinguished between automation and augmentation “empirically,” using estimates of the extent to which observed queries either substitute or complement for tasks in a given occupation. “These findings are consistent with automative uses of AI substituting for labor while augmentative uses do not,” the

This is similar to a line adopted

Stanford’s analysis rules out several other explanations, such as COVID-era disruptions or interest-rate shocks. The effects only emerged after late 2022, coinciding with rapid generative AI adoption, and are not limited to computer-related jobs, the

For workers aged 22 to 25, researchers say they found a decline in relative employment for the most AI-exposed quintiles compared to the least exposed quintile, a “large and statistically significant effect.” Other age groups had much smaller and statistically insignificant estimates, on the other hand.

Fears of collapsing income related to AI may be overblown, the study says, finding that the adjustment in the labor market is happening largely through decreased employment rather than lower wages. Pay rates have not shifted dramatically, according to Stanford, with “little difference in annual salary trends

Finally, the Stanford team argues these facts are largely consistent across various samples, with patterns in the data appearing “most acutely starting in late 2022, around the time of rapid proliferation of generative AI tools.”

The