AI Is Hitting Entry-Level Jobs Hardest. What Early-Career Professionals Can Do

By Julien Boubel | 2026-11-01

New Stanford research finds employment for 22 to 25 year olds in AI-exposed jobs is about 19% below trend, while experienced workers show no gap. A look at the data and some practical next steps.

TL;DR - Employment for workers aged 22 to 25 in highly AI-exposed occupations is about 19% below where it would be had it kept pace with less-exposed jobs. A year ago the gap was 15%. - Experienced workers in the same occupations show no comparable gap. - The shortfall is concentrated in jobs where AI takes over tasks, rather than jobs where it helps people do them. - The researchers see no sign of widespread job losses across the economy. What the Stanford team found Erik Brynjolfsson, Bharat Chandar and Ruyu Chen at the Stanford Digital Economy Lab have been tracking young workers in AI-exposed jobs using payroll data from ADP. Their August 2026 update puts the employment gap for 22 to 25 year olds at about 19%. That is measured against where employment would be if it had grown at the same rate as for people the same age in less-exposed jobs. It's a shortfall against a trend, not a 19% drop in headcount. Older workers look very different in the same data. Among experienced workers in occupations that depend on tacit knowledge, employment has gone up. In jobs where AI is mostly used to support people rather than replace their tasks, employment is flat or rising, and that holds especially for more experienced staff. The authors are careful about what this proves. They describe these as descriptive patterns rather than causal estimates, and they say plainly that they don't see economy-wide displacement. Still, the gap has widened for a second year in a row, which is reason enough for anyone starting out to pay attention. Why entry-level work is more exposed Think about what a typical first job involves. Drafting the first version of a report, summarising meetings, pulling together research, cleaning up a spreadsheet, answering routine customer

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