Stanford Study Reveals Sharp Employment Gap for Young Workers in AI-Exposed Jobs
Stanford Digital Economy Lab's revised analysis finds employment among workers aged 22–25 in highly AI-exposed occupations stands 19% below expected levels as of June 2026.
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Stanford Releases Updated ‘Canaries in the Coal Mine’ Analysis
The Stanford Digital Economy Lab released a revised version of “Canaries in the Coal Mine? Six Facts About the Recent Employment Effects of Artificial Intelligence” on August 12, 2026. The study, which tracks employment using payroll data from ADP since the release of ChatGPT, finds no widespread, economy-wide job displacement associated with AI. However, the findings reveal significant generational and occupational divides.
Young Workers Bear the Brunt of AI Disruption
Employment among workers ages 22–25 in highly AI-exposed occupations stands about 19% below where it would be if it had kept pace with employment among similarly aged workers in less-exposed occupations, as of June 2026. This gap has widened considerably: it stood at 15% at the July 2025 data vintage.
In absolute terms, employment of workers ages 22–25 in the two most AI-exposed quintiles fell about 11% between November 2022 and June 2026. By contrast, employment of workers ages 22–25 in the three least AI-exposed occupational quintiles grew about 10% over the same period.
Experienced workers (older than 25) show no comparable AI-related employment gap, suggesting the challenge is concentrated among entry-level job seekers.
Hiring Freezes, Not Layoffs
The divergence in young-worker employment appears to operate primarily through reduced hiring rather than increased separations (layoffs). Employment declines are concentrated in occupations where AI usage tends to automate human tasks; in occupations where AI complements workers, employment is flat or rising, particularly among experienced workers.
Knowledge Type Matters
Employment has declined among young workers in occupations relying heavily on codified knowledge (formal, standardised, documented knowledge teachable via textbooks), while increasing among experienced workers in occupations relying on tacit knowledge. The AI employment adjustment is showing up primarily in employment levels rather than in base pay.
Women Face Greater AI Exposure
Women face greater AI exposure on average than men, according to the revised Canaries study.
New Monitoring Dashboard Launched
The Stanford Digital Economy Lab has launched the AI Economic Indicators project, which includes a Canaries Dashboard that will update key employment results monthly.
Independent Confirmation
U.S. Census Bureau government administrative data show broadly consistent raw descriptive patterns by age and industry with the Canaries study findings (Tucker 2026, CES-WP-26-27).
Source: Stanford Digital Economy Lab
Developments since publication
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There is no widespread, economy-wide job displacement associated with AI, according to payroll data from ADP analysed by Stanford Digital Economy Lab researchers Erik Brynjolfsson, Bharat Chandar, and Source
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Women face greater AI exposure on average, identified as an important source of heterogeneity in the Stanford Digital Economy Lab's updated Canaries in the Coal Mine paper. Source
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Women face greater AI exposure on average than men, according to the Stanford Digital Economy Lab's updated analysis. Source
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The Stanford Digital Economy Lab launched the AI Economic Indicators project, which includes a Canaries Dashboard that updates key employment-by-AI-exposure results every month using ADP payroll data. Source
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The revised 'Canaries in the Coal Mine' paper was authored by Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen of the Stanford Digital Economy Lab, using ADP payroll data. Source
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A Stanford Digital Economy Lab working paper released in November 2025 found that workers aged 22 to 25 in the most AI-exposed occupations experienced a 16% relative decline in employment after the sp Source
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