Stanford Digital Economy Lab
Stanford University research lab directed by Erik Brynjolfsson; showed AI suppresses 34 hires per declared layoff.
Stanford Digital Economy Lab's finding that AI suppresses roughly a million US hires a year became the field's reference figure by 23 July 2026, when SAP cited the 34-to-1 ratio to explain why its hiring freeze would show up nowhere in job-cut statistics.
Last refreshed: 27 July 2026 · Appears in 1 active topic
If AI is suppressing 34 hires for every announced layoff, how big is the real jobs hole?
Timeline for Stanford Digital Economy Lab
Estimated roughly 34 suppressed hires for every declared AI layoff
AI: Jobs, Power & Money: SAP freezes research hiring for a yearPublished the We Must Act Now statement
AI: Jobs, Power & Money: 16 Nobel laureates sign Stanford's alarmMentioned in: Challenger: US cuts fall 53% in June
AI: Jobs, Power & MoneyMentioned in: AI cuts hit record 38,579 in May
AI: Jobs, Power & MoneyMentioned in: UK youth jobless rate hits 12-year high
AI: Jobs, Power & MoneyBackground
Stanford Digital Economy Lab is a research lab at Stanford University directed by Erik Brynjolfsson, studying the labour-market effects of AI adoption. Its central methodology reads suppressed hiring, jobs never advertised because of AI, rather than declared layoffs, as the dominant channel through which AI is displacing US workers, arguing that headline layoff counts understate the true scale by an order of magnitude.
The Lab periodically extends its findings into public-facing tools and statements, coordinating with other academics and economists to keep pressure on policymakers and central data agencies that have largely Left the measurement gap unfilled. Its age-concentration findings, that younger workers in AI-exposed occupations have fared markedly worse than older colleagues in the same roles, are the piece of its research hardest to explain through non-AI channels, and give the Lab an outsized role in a debate where the Bureau of Labor Statistics has yet to publish an equivalent federal figure.
Suppressed hiring outweighs declared AI layoffs
On 10 April 2026 the Lab applied the JOLTS 3.1% hiring rate, the lowest since April 2020, to the 158.6m nonfarm US workforce and calculated that AI is preventing roughly 950,000 to 1 million annual hires against the 2023 pace . Against 27,645 declared AI layoffs through March, that works out to about 34 hires suppressed for every one declared layoff, and workers aged 22 to 25 in AI-exposed roles sat 16% below their late-2022 employment level.
The 34:1 finding has become the field's reference ratio: Challenger's May count of 38,579 AI-attributed cuts, the largest monthly total of 2026, reasserted it , and by 23 July SAP was citing the same figure directly to explain why its year-long research hiring freeze would not appear in official job-cut statistics .