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AI: Jobs, Power & Money
17JUL

Goldman counts 25,000 jobs lost monthly

3 min read
14:01UTC

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

EconomicDeveloping
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
Read original
Different Perspectives
Stanford's 'We Must Act Now' signatories
Stanford's 'We Must Act Now' signatories
More than 200 academics, including 16 Nobel laureates, published a 13 July letter warning of AI-driven labour disruption, citing Daron Acemoglu's NBER estimate that AI's total factor productivity gain stays under 0.66% over ten years. The letter's own cited economics sit well below Goldman Sachs Research's 1.5-percentage-point estimate published the same week.
Germany / the Bundesrat
Germany / the Bundesrat
Germany's Bundesrat acted on the EU AI Act's employment provisions on 10 July, more than a year ahead of the Act's 2 December 2027 enforcement deadline. Germany is moving on statutory AI-employment disclosure while the US Congress and Federal Reserve have no equivalent instrument.
Indian IT services sector (TCS, HCLTech, Wipro)
Indian IT services sector (TCS, HCLTech, Wipro)
TCS cut 19,271 roles and HCLTech cut 3,292 in the same reporting week that Wipro's headcount rose by 888 under its own zero-fresher-hiring pledge for FY27. The divergence shows attrition, not layoffs, is how India's outsourcers absorb AI-driven project compression while their net headcount numbers stay ambiguous.
Federal Reserve
Federal Reserve
Barr said on 14 July there is little evidence of AI displacement, citing a 43-versus-10 adoption gap by education; Cook said the next day the dire predictions have not come to fruition, her text carrying none of the bond-spread language she used in May. The Fed reads AI's labour effect through national aggregates, where four banks' cuts remain statistically invisible.
Barclays
Barclays
Barclays economist Pooja Sriram flagged a 28,000-a-month bleed in finance and information roles the same week Microsoft disputed that AI drove its own 4,800 cuts. The bank treats Challenger's AI-attribution share as a lagging indicator against faster erosion visible in raw labour-market data.
European Commission
European Commission
Brussels deferred the Digital Omnibus's Annex III employment-compliance deadline from 2 August 2026 to December 2027, even as California advanced three binding AI-hiring bills the same week. The 17-month delay leaves EU workers without the algorithmic-hiring safeguards the regulation already promises.