Could AI Layoffs Leave The Same Scars As Earlier Tech Shocks?

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Workers likely displaced by AI since 2025 took about a month longer to find new jobs and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers, according to a Goldman Sachs note reported by Fortune. The estimates raise concerns that AI-related job losses could carry costs beyond the initial layoff, though the note is not public and Goldman’s method identifies likely displacement rather than confirming that AI caused each job loss.

Goldman economist Pierfrancesco Mei wrote the client note dated October 29, Fortune reported the following day. The publication said it quoted the note directly; the note itself was not publicly available for independent review. The figures should therefore be treated as reported findings, not as a government count of workers whose jobs were definitively eliminated by AI.

Because government surveys do not ask whether AI caused a respondent’s job loss, Goldman constructed an estimate using the Labor Department’s Displaced Worker Supplement to the Current Population Survey. As described in the source account, the analysis covered more than 15,000 people who lost jobs between 2016 and 2025. It combined occupational AI exposure, industry adoption and whether a position was eliminated; workers in the top 30% of the resulting score were classed as “likely AI-displaced.” Goldman reportedly found no significant difference from other laid-off workers for job losses before 2023, when AI adoption began to rise.

For job losses since 2025, Fortune’s account says the likely AI-displaced group took about one month longer to find work and was about 10 percentage points more likely to be unemployed one year after losing a job. Workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, versus about three weeks for those under 35. The report also says more displaced workers changed occupations or industries, but some who were rehired moved into jobs with similar or higher AI exposure.

The Cost Can Outlast the Layoff

The findings put attention on what happens after a job ends: the duration of unemployment, the pay and stability of the next role, and whether workers can stay in their occupation. A layoff count alone cannot show those longer-term effects. If the reported differences hold up, workers facing AI-related displacement may need more time and support to regain stable employment than other laid-off workers.

Goldman’s publicly available historical research provides a warning, not proof that the same outcomes will follow every AI-related layoff. Its work on technology-related displacement found that workers took about a month longer to find work, lost more than 3% in real pay when rehired, and had nearly 10 percentage points less real earnings growth over the following decade than workers who were not laid off. These figures refer to historical technology displacement and should not be confused with the new note’s estimates for likely AI displacement.

The difference matters to workers, employers and policymakers because the burden may not be evenly shared. Both the reported note and government figures point to greater difficulty for older workers. The source also says historical Goldman data link retraining within three years to about 2 percentage points more real wage growth over ten years and a roughly 10-point lower chance of becoming unemployed again. That association does not establish that training alone caused the better outcomes.

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Four Decades of Job Displacement Data

The new estimate is set against research Goldman published in its June 2026 “Top of Mind” report and a September summary. Mei and colleagues Jessica Rindels and David Mericle examined more than 300 occupations over several decades, using National Longitudinal Surveys that have followed more than 20,000 workers through their careers. They compared people in occupations more exposed to technological change with those in stable or growing occupations.

That research found a persistent employment and earnings penalty after technology-related job losses: slower reemployment, lower real pay on return, and weaker earnings growth over the next decade. The source account also cites Bureau of Labor Statistics data on long-tenured workers who returned to full-time work: about 49% earned as much as before or more, compared with about 62% two years earlier. The comparison is reported as a change over two years; it does not by itself establish that AI caused the decline.

Government data cited in the source show age differences among long-tenured workers who had been displaced, regardless of the reason. By January 2026, 72.9% of workers aged 25 to 54 were working again, compared with 57.3% of those aged 55 to 64. Those figures describe all laid-off workers in the specified groups, not only people affected by AI.

““comparable in magnitude””

— Pierfrancesco Mei, Goldman Sachs economist, as quoted in Fortune

AI’s Role Is Hard to Isolate

The central limitation is that the AI-displacement figures are estimates. The method classifies workers using exposure, industry adoption and job elimination, rather than asking each person or employer whether AI caused the job loss. A job in an AI-exposed occupation may disappear for other reasons, and the reported results do not establish that AI was the sole cause.

The note is also not public. Fortune reported its figures and quoted Goldman, but readers cannot inspect the full analysis, assumptions or detailed tables from the source material. The sample and method described do not settle how the results vary by education, region or other characteristics; Mei reportedly said those effects were too early to assess. Nor do the findings establish how long the current AI-related differences will persist.

Goldman’s public historical research concerns earlier technological change across many occupations and decades. It offers a comparison, but it cannot show that AI will produce the same wage and employment outcomes. The source says Goldman expects AI-related job losses to speed up if the economy slows and that displacement costs are larger in downturns; this is an economic expectation, not a confirmed forecast of when or how many additional jobs will be lost.

Watch the Next Employment Data

The next test will be whether follow-up data show that the reported gaps in job-search time and unemployment continue as AI adoption spreads. A clearer assessment will require more observations over time and information that distinguishes AI-caused job losses from layoffs driven by other business or economic changes.

Readers should also watch for further Goldman research or a public release of the client note, along with new Labor Department data on displaced workers, reemployment and pay. The current evidence does not specify a date for additional analysis. A slowing economy could complicate the picture: Goldman’s reported assessment is that downturns increase the costs of displacement, but the scale and timing of any additional AI-related losses remain uncertain.

Key Questions

What did Goldman Sachs report about workers likely displaced by AI?

Fortune reported that workers Goldman classified as likely AI-displaced since 2025 took about a month longer to find new work and were roughly 10 percentage points more likely to remain unemployed a year later than other laid-off workers. The estimate comes from a client note that was not publicly available.

Does the analysis confirm that AI caused those job losses?

No. The analysis used an indirect score based on occupational AI exposure, industry adoption and job elimination. It estimates which workers were likely displaced by AI; it does not confirm the cause of each person’s layoff.

What do earlier technology layoffs suggest about longer-term effects?

Goldman’s public historical research found that workers displaced by technology took longer to find work, lost more than 3% in real pay on reemployment, and had nearly 10 percentage points less real earnings growth over the next decade than workers who were not laid off. Those historical results do not prove AI will produce identical effects.

Are older workers more affected?

The reported Goldman note says workers aged 35 and older took about five weeks longer than comparable laid-off workers to return to full-time work, compared with about three weeks for those under 35. Separate government figures cited in the source also show lower reemployment among long-tenured workers aged 55 to 64 than among those aged 25 to 54.

What remains unknown?

The note is not public, AI’s role in individual job losses cannot be confirmed from the method described, and it is too early to know how effects vary by education or region or how long they will last. The source also gives no confirmed timetable or count for future AI-related layoffs.

Source: ThorstenMeyerAI.com