Younger or entry-level workers are feeling the most heat from displacement caused by artificial intelligence, yet more experienced workers are doing just fine, thank you. Real-world experience in professions may be a quality that AI is incapable of replicating, a new study suggests.
The updated research out of Stanford University continues to find no widespread displacement of jobs due to AI, but there is continued pain for entry-level workers. The employment gap for young workers versus has widened from 15% to 19% over the past year, the researchers find.
These conclusions are an update to a study published a year ago, titled “Canaries in the Coal Mine?” co-authored by Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen. The research is based on payroll data from ADP and employment data from the U.S. Bureau of Labor Statistics. The increased gap “appears to operate primarily through reduced hiring of young workers rather than increased separations,” they add. (Full paper here.)
Overall, looking across all job categories and age groups, “we do not see widespread, economy-wide job displacement associated with AI,” Brynjolfsson and his colleagues observe. “However, young workers in AI-exposed occupations are increasingly falling behind their less-exposed peers.” Experienced workers show no signs of job losses, they added.
There is a notable distinction between codified and tacit knowledge among workers, the researchers found. “Employment has declined among young workers in occupations that rely heavily on codified knowledge: formal, standardized, documented knowledge that can be taught through education, textbooks, or written procedures,” they observed.
“In contrast, employment has increased among experienced workers in occupations that rely more heavily on tacit knowledge acquired through practice, mentorship, and repeated exposure to real situations.”
Tellingly, generative AI “is particularly effective at reproducing and applying knowledge that has already been encoded in text and other digital information, while experience-based knowledge remains harder to replicate,” the researchers conclude.
It’s not clear of AI is to blame for any occupational fallbacks, the researchers cautioned. “The data alone cannot establish how much of the divergence was caused by generative AI rather than other forces affecting the labor market.” The researchers controlled for interest rate changes, education levels, and remote work trends, and concluded it’s likely AI contributes to the occupational shifts studied.
Still, there is no evidence yet of any sort of a job “apocalypse” due to AI, as has been widely predicted over the past year. “The data suggests a possible mild slowdown in employment growth for the most exposed jobs,” the Stanford researchers stated. “Average employment in the ADP sample rose by about 6% between November 2022 and June 2026, while employment for the most exposed quintile grew by about 4%. These results are consistent with recent evidence that AI-exposed jobs have not seen widespread employment declines. This aggregate stability is itself informative: claims of economy-wide AI-driven job losses are not visible in payroll data through June 2026.”
