Goldman Sachs Raises AI Job Displacement Estimate to 9% of US Workers, Up From 6% to 7%

On Oct. 22, Goldman Sachs Research put a hard number on what the AI transition could cost workers.

The bank estimates AI could temporarily push about 9% of US workers out of their jobs. That figure assumes AI lifts productivity by 15%. In headcount terms, Goldman puts it at up to 15 million people over roughly a decade.

It is a step up. The bank's previous estimate put displacement at 6% to 7% of the workforce.

How Goldman built the number

The research is led by Goldman economist Joseph Briggs. His team did not lean only on net unemployment figures, which can hide heavy churn underneath.

The US economy already creates and destroys roughly 30 million jobs every year, according to the research. Goldman's historical analysis found that each 1% productivity gain from technology raises job destruction rates by about 0.5 to 0.6 percentage points over two years.

Run a 15% productivity boost through that formula and you land at the roughly 9% displacement scenario.

Who is exposed

Past automation waves hit factory floors. Goldman expects this one to land mostly on white-collar and entry-level roles. The bank names technology, consulting, graphic design and administrative support as exposed fields.

Briggs said the effect is already showing up in the data. He noted AI is shaving about 10,000 to 15,000 jobs per month off payroll growth in susceptible sectors such as tech and management consulting.

That is a drag on hiring, not a mass layoff event.

The macro picture

Goldman forecasts the US unemployment rate could climb by as much as 0.6 percentage points because of AI adoption. The researchers expect that bump to ease within a few years as the labor market adjusts.

The bank's optimism rests on history. Around 85% of US job growth over the past 80 years came from occupations that did not previously exist, created by new technology. Goldman expects generative AI to follow a similar pattern.

It also projects the technology could raise annual US labor productivity by about 1.5 percentage points once fully adopted. The effects would vary widely across job categories.

The caveats

Goldman's number is a forecast over about a decade, built on an assumed 15% productivity gain. The bank calls the displacement temporary, and the 15 million headcount is an upper bound.

Market commentary on the report, including from 24/7 Wall St., treated it as the cost side of a productivity story that equity markets have been paying up for. That framing is the commentators' own. Goldman's research describes the displacement as transitional, with productivity gains raising broader economic output over time. The timing and depth of that transition remain the open question for labor markets.

Why entry-level workers are the pressure point

Entry-level white-collar roles have traditionally been the first rung on the career ladder, and Goldman's research suggests that rung is getting wobbly. If companies use AI to handle junior tasks, the pipeline that trains future senior staff could thin out.

What to watch

The key indicators are the monthly payroll drag Briggs flagged and whether new AI-related occupations start appearing fast enough to absorb displaced workers. If the 10,000 to 15,000 monthly figure grows, the transition could prove rockier than Goldman's base case.

The upward revision from 6% to 7% to about 9% is itself a signal. Goldman's researchers now see a bigger wave of disruption than they did before, even as they continue to argue the tide will eventually turn. If new occupations take longer to appear than displaced ones take to vanish, the 0.6-point rise in unemployment could last longer than the few years Goldman expects. If the 15% productivity gain never materializes, the displacement math shrinks with it.