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Goldman counts 25,000 jobs lost monthly

3 min read
12:41UTC

A bottom-up displacement model from Goldman Sachs calculates AI is eliminating three times more jobs per month than appear in any official tally.

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Key takeaway

Announced AI layoffs undercount actual displacement by roughly three to one.

Goldman Sachs published research on 6 April calculating that AI substitutes 25,000 US jobs per month and creates roughly 9,000 through augmentation, a net loss of 16,000 positions monthly 1. Over twelve months that implies approximately 300,000 actual substitutions, against the 107,094 cumulative AI-attributed cuts that Challenger, Gray & Christmas has counted since 2023 . The gap is roughly three to one: for every job cut that appears in the public tally, Goldman's model suggests two more disappear without a press release.

Goldman's bottom-up model resolves a contradiction this topic has tracked since Update #3. The Atlanta Fed projected 502,000 AI-attributed cuts for 2026 , while the NBER found 90% of firms report zero employment impact . Goldman explains the gap: most displacement runs through attrition, contract non-renewal, and restructured job descriptions rather than announced layoffs. Workers vanish from roles that are never re-posted.

The mechanism falls hardest on entry-level positions. A study of 62 million resumes found AI-adopting firms cut entry-level postings by 15% while senior roles held flat ; the Dallas Fed confirmed the losses concentrate among workers under 25 through collapsed job-finding rates, not firing . Fortune and Columbia University research showed 75% of displaced Americans never file for unemployment insurance , meaning three quarters of the newly unemployed are invisible to the claims system policymakers depend on.

Deep Analysis

In plain English

There are two ways to count jobs lost to AI. The first is to count the announcements: when a company says publicly that it is cutting jobs because of AI. These announcements have now topped 107,000 since 2023. Goldman Sachs has tried to count the second way: how many jobs are actually disappearing through quieter means. Workers whose contracts are not renewed. Roles that are quietly restructured. Positions that open up when someone leaves and are then never re-posted. Goldman's estimate is 25,000 per month are being replaced by AI, with about 9,000 new positions created elsewhere, leaving a net loss of 16,000 every month. If Goldman is right, the announced figure of 107,000 total is roughly one-third of the real number. The other two-thirds disappear without a press release.

Deep Analysis
Root Causes

Goldman's model identifies attrition as the primary transmission mechanism: when workers leave roles that AI can perform, those positions are quietly closed rather than re-posted. Dell's annual report documented this precisely, shedding 27% of its workforce from 133,000 to 97,000 over three years through attrition and limited hiring rather than public announcements.

The measurement gap has structural causes. Challenger, Gray & Christmas counts only layoffs where companies explicitly cite AI as the reason, which is roughly 25% of total announced cuts in March 2026. Companies have legal and reputational incentives to attribute cuts to 'restructuring' or 'efficiency' rather than AI: it avoids triggering AI-specific disclosure requirements and reduces union mobilisation risk.

A Hamilton Project synthesis (2026) noted that job posting declines in AI-exposed occupations began in 2022, before ChatGPT's November 2022 release, correlating with rising interest rates. This complicates causal attribution: the attrition Goldman measures may partly reflect a rate cycle rather than pure AI substitution.

What could happen next?
  • Consequence

    If Goldman's 3:1 ratio between actual and announced displacement holds, cumulative AI-driven job losses since 2023 may already exceed 300,000, not the 107,000 in the Challenger dataset.

  • Risk

    Policy responses calibrated to the Challenger headline figure may be addressing one-third of actual displacement, leaving the majority invisible to labour market interventions.

First Reported In

Update #5 · The model they won't release

Fortune (reporting Goldman Sachs research)· 10 Apr 2026
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