# Is AI reducing jobs for young workers?

**In one narrow group, the data points that way. Across the whole labour market, there is no clear sign yet.** The two most cited studies look at different slices of the data, and both can be right.

**Stanford's finding (ADP payroll records).** Stanford's Digital Economy Lab (Brynjolfsson, Chandar and Chen, revised August 2026, data to June 2026) works from ADP payroll records:

- Employment of **22 to 25 year olds** in the two most AI-exposed fifths of jobs **fell about 11%** between November 2022 and June 2026.

- The same age group in the three least-exposed fifths **grew about 10%**.

- Measured against their less-exposed peers, young workers in exposed jobs stand **19% below** where they would be had they kept pace. That gap was 15% a year earlier.

- Experienced workers show no comparable gap, and the declines are in jobs where AI automates the work. Where AI complements workers, employment is flat or rising.

The authors call these early, descriptive indicators and say they do not estimate a causal impact of AI. Their sample is a fixed panel of ADP client firms that over-represents manufacturing, wholesale and larger firms, and the paper says overall employment remains robust.

**Yale's finding (the whole labour market).** The Yale Budget Lab tracker (updated 15 September 2026) reports that the occupational mix is not yet changing in ways that clearly align with AI, that measures of AI usage show no connection to changes in employment or unemployment, and that a synthetic difference-in-differences analysis does not yet clearly indicate an AI-related footprint.

**Why both can hold.** 22 to 25 year olds are under a tenth of Stanford's sample, so a fall in that group can be real and still too small to show in economy-wide numbers.

**What Amar sees on the ground in India:** in the smaller businesses he works with, fewer interns and freshers, fewer backfills, smaller dev teams, and more work done in-house by existing teams using AI coding tools.

Sources: Stanford's [Canaries in the Coal Mine?](https://digitaleconomy.stanford.edu/publication/canaries-in-the-coal-mine-six-facts-about-the-recent-employment-effects-of-artificial-intelligence/) paper and its monthly [Canaries Dashboard](https://digitaleconomy.stanford.edu/project/indicators/canaries-dashboard/) with downloadable data, and Yale Budget Lab's [Tracking the Impact of AI on the Labor Market](https://budgetlab.yale.edu/research/tracking-impact-ai-labor-market). The wider US jobs picture: [how many jobs the US needs each month](https://www.tigzig.com/agents-faq/how-many-jobs-does-the-us-need-to-add-each-month). Full analysis with the deck: [https://www.tigzig.com/post/adp-young-workers-ai-exposed-jobs-oct2026](https://www.tigzig.com/post/adp-young-workers-ai-exposed-jobs-oct2026).

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Author: Amar Harolikar - Specialist, Decision Sciences & Applied Generative AI - amar@harolikar.com - https://www.linkedin.com/in/amarharolikar
Source: https://www.tigzig.com/agents-faq/is-ai-reducing-jobs-for-young-workers
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