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.
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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Women face greater AI exposure on average than men, according to the Stanford Digital Economy Lab's updated analysis. Source
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So far, adjustment to AI exposure among young workers is showing up primarily in employment levels rather than base pay. Source
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AI-related roles are being created in Ireland at two to three times the pace observed in neighbouring countries, according to a report from the Expert Group on Future Skills Needs (EGFSN). Source
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Close to 12% of job postings in Ireland reference AI skills, compared to 4% in the US and 6% in the UK. Source
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The share of Irish job postings referencing AI skills fluctuated between 4% and 6% from 2019 to 2023, and has since doubled, with a marked increase over the past year. Source
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Usage of AI by large enterprises in Ireland rose from 31.2% to 57.3% between 2021 and 2025, according to Eurostat data cited in the EGFSN report. Source
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AI adoption by small firms in Ireland rose from 6.1% to 16.8% between 2021 and 2025, according to Eurostat data cited in the EGFSN report. Source
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AI adoption by medium-sized firms in Ireland rose from 13.2% to 28% between 2021 and 2025, according to Eurostat data cited in the EGFSN report. Source
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The EGFSN report warned that the gap between large and small enterprise AI adoption points to a risk of a two-speed economy, in which larger firms capture a disproportionate share of AI-related produc Source
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The EGFSN report was authored by Diarmaid Smyth. Source
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The adjustment for young workers in AI-exposed occupations appears to operate primarily through reduced hiring rather than increased separations. Source
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Employment has declined among young workers in occupations that rely heavily on codified knowledge, while employment has increased among experienced workers in occupations relying more on tacit knowle Source
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So far, AI-related employment adjustment is showing up primarily in employment levels rather than in base pay (which excludes bonuses, equity, and other variable pay). 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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An Anthropic report from March 2026 provides suggestive evidence consistent with a relative employment decline for young workers in AI-exposed occupations. Source
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The MIT Technology Review article was authored by Georgios Petropoulos, an assistant professor at the USC Marshall School of Business whose research focuses on implications of information technologies Source
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Employment declines for young workers are concentrated in occupations that rely heavily on codified knowledge; employment has increased among experienced workers in occupations relying on tacit knowle Source
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So far, AI-related labour market adjustment is showing up primarily in employment levels rather than in base pay. Source
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The divergence in employment between AI-exposed and non-exposed young workers remains when technology firms and computer occupations are excluded, and when controlling for interest-rate exposure and r Source
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The U.S. Census Bureau's administrative data show broadly consistent descriptive patterns by age and industry with the Stanford ADP findings, per Tucker (2026). Source
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Covalen has said it is cutting around 700 roles at its Irish operations. Source
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Meta is cutting approximately 20% of its Irish workforce, double the planned global average cut at the company. Source
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TikTok is considering cutting approximately 300 staff in Ireland, in a restructure impacting its AI data service and operations team. Source
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More than 6% of Ireland's workforce is employed in the tech sector, higher than the EU average. Source
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Employment in ICT among the under-30s in Ireland dropped by almost one third between 2023 and 2025, according to a government analysis. Source
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In the first quarter of 2026, overall jobs in Ireland's tech sector fell almost 11% year-on-year. Source
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Bloomberg Economics estimates that 30% of workers in Ireland are likely to be meaningfully affected by AI, above the 27% advanced-economy average. Source
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Ireland's unemployment rate is below the euro-area average as of July 2026. Source
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