Goldman Sachs Research estimates that artificial intelligence could temporarily displace roughly 9% of the US workforce. The projection assumes AI lifts productivity by 15% and, in headcount terms, translates to as many as 15 million workers over a period of roughly a decade. The updated figure also marks an increase from the bank's earlier estimate, which had pegged potential displacement at 6% to 7% of the workforce.

The Projection and Its Methodology

The research is led by Goldman Sachs economist Joseph Briggs. Its central premise is straightforward: when machines make work faster, some existing jobs disappear before new ones emerge to take their place, producing a gap even as the economy adjusts.

Rather than relying solely on net unemployment figures, the team built its estimate from historical patterns of technology-driven job disruption. According to the research, roughly 30 million jobs are created and destroyed in the United States every year, a level of churn that unfolds largely beneath the surface of headline unemployment data — a reminder that large-scale job turnover is a routine feature of the US labor market rather than an anomaly.

Goldman's historical analysis identified a link between productivity gains and that churn: each 1% increase in productivity — a measure of output per hour worked — from technology lifts job destruction rates by about 0.5 to 0.6 percentage points over two years. Applying a 15% productivity boost to that framework yields the roughly 9% displacement scenario.

Which Roles Are Most Exposed

Unlike past waves of automation that struck factory floors, the impact of AI is expected to land mostly on white-collar and entry-level positions. Goldman identifies technology, consulting, graphic design, and administrative support as exposed fields.

Briggs said the effect is already showing up in the data rather than remaining a forward-looking estimate. He noted that AI is shaving about 10,000 to 15,000 jobs per month off payroll growth in susceptible sectors such as technology and management consulting.

The bank also sees broader macroeconomic effects. Goldman forecasts that AI adoption could push the US unemployment rate up by as much as 0.6 percentage points, though the researchers expect that bump to ease within a few years as the labor market adjusts.

Why Goldman Calls It Temporary

The bank's outlook rests on history. Around 85% of US job growth over the past 80 years has come from occupations that did not previously exist, created by new technology.

Goldman expects a similar pattern with generative AI. The bank projects that the technology could raise annual US labor productivity by about 1.5 percentage points once fully adopted, though the effects would vary widely across job categories.

What This Means for Workers

For workers, the most important detail may be the shape of the disruption. Entry-level white-collar roles have traditionally served as the first rung on the career ladder, and Goldman's research suggests that rung is becoming less secure. If companies use AI to handle junior tasks, the pipeline that trains future senior staff could thin out.

The key indicators to watch are the monthly payroll drag Briggs flagged and whether new AI-related occupations begin appearing quickly enough to absorb displaced workers. If the 10,000 to15,000 monthly figure grows, the transition could prove rockier than Goldman's base case.

Goldman's upward revision, from 6% to 7% to about 9%, is itself a signal. The bank's researchers now see a larger wave of disruption than they did previously, even as they continue to argue the tide will eventually turn.