How Will AI Affect the Global Workforce?

Innovation related to artificial intelligence (AI) could displace 6-7% of the US workforce if AI is widely adopted. But the impact is likely to be transitory as new job opportunities created by the technology ultimately put people to work in other capacities, according to Goldman Sachs Research.

“A recent pickup in AI adoption and reports of AI-related layoffs have raised concerns that AI will lead to widespread labor displacement,” Joseph Briggs, who co-leads the Global Economics team in Goldman Sachs Research, and economist Sarah Dong, write in a report. “While these trends could broaden as adoption increases, we remain skeptical that AI will lead to large employment reductions over the next decade.”

Temporary unemployment caused by the adoption of labor-saving technologies typically increases the US jobless rate by 0.3 percentage point with every 1 percentage point gain in technology-driven productivity growth. However the impact is usually fleeting—such job displacement tends to disappear after two years, Briggs and Dong write.

How will AI impact labor productivity?

Our economists estimate that generative AI will raise the level of labor productivity in the US and other developed markets by around 15% when fully adopted and incorporated into regular production. That would translate into a half-percentage-point rise in the unemployment rate above its trend during the AI transition period, though that impact could be higher if AI adoption is more frontloaded than they assume.

As part of their research, the team examined more than 800 occupations to assess whether AI productivity gains will translate into job displacement. The 6-7% estimate for job displacement from AI is the team’s baseline assumption, but they write that displacement rates could vary from 3% to 14% under different assumptions.

What could AI mean for unemployment?

There are two ways in which AI could hypothetically lead to an increase in unemployment. The first is if AI capabilities advance to a point where human input becomes redundant for many types of production, leading to persistent structural unemployment.

This outcome is unlikely, according to Goldman Sachs Research, because technology change tends to boost demand for workers in new occupations. That can take place either directly through new jobs that emerge from technological change or indirectly by triggering an overall boost in output and demand. Approximately 60% of US workers today are in occupations that didn’t exist in 1940, implying that more than 85% of employment growth since then has been from technology-driven job creation.

“Predictions that technology will reduce the need for human labor have a long history but a poor track record,” Briggs and Dong write.

However there could also be a period of higher unemployment while AI-displaced workers are looking for new jobs. “Frictional unemployment is not unique to AI and occurs during most periods of rapid technological change,” Briggs and Dong write. Historically, upheaval from technological innovation has proven to be temporary—after two years there is no noticeable impact.

Is AI already causing job losses?

Recent commentary by some public companies suggests the labor market is already experiencing effects related to AI. Executives from the technology and finance sectors say they are seeing efficiency gains from generative AI that are sufficient to slow their hiring, especially in operational and back-office capacities.

That said, AI adoption remains relatively low, especially among midsized and small enterprises. While adoption rates have accelerated recently, the vast majority of companies have not incorporated AI into regular workflows. In a recent US survey, only 9.3% of companies reported that they had used generative AI in production during the last two weeks.

To date, low adoption is limiting the overall labor-market impacts from AI, according to Goldman Sachs Research. Our economists found no significant statistical correlation between AI exposure and a host of economic measures, including job growth, unemployment rates, job finding rates, layoff rates, growth in weekly hours, or average hourly earnings growth.

What industries are being affected by AI?

Still, there are early signs of disruption in specific industries. Employment growth in industries such as marketing consulting, graphic design, office administration, and telephone call centers has fallen below trend amid reports of reduced labor demand due to AI-related efficiency gains.

In addition, employment growth in technology-sector occupations such as computer systems design, software publishing, and web search portals has slowed sharply. Tech employment as a share of overall employment has decreased steadily since November 2022.

“While some of the decline can be attributed to payback from over-hiring during the pandemic, tech’s employment share has now fallen below its (remarkably linear) pre-pandemic trend, a pattern probably related to AI automation,” Briggs and Dong write.

So far, younger tech workers appear to be disproportionately affected. Unemployment among 20- to 30-year-olds in tech-exposed occupations has risen by almost 3 percentage points since the start of 2025, notably higher than for their same-aged counterparts in other trades and for overall tech workers as well. This corroborates anecdotal reports that generative AI is contributing to hiring headwinds facing recent college graduates in technology.

Despite compelling evidence of AI’s impact on hiring, the range of affected positions remains narrow. If current AI use cases were expanded across the economy, Goldman Sachs Research estimates that just 2.5% of US employment would be at risk of displacement.

Which jobs are most at risk for AI automation in the future?

But what about tomorrow? To help assess the risk of AI-related job loss across industries in the future, our researchers looked at factors such as task repetitiveness, the consequences of errors from AI tools, the connections between tasks, and the value of AI-exposed tasks compared to prevailing wages.

They conclude that occupations at the highest risk of being displaced by AI in the coming years include computer programmers, accountants and auditors, legal and administrative assistants, customer service representatives, telemarketers, proofreaders and copy editors, and credit analysts. Those at the least risk of being displaced are air traffic controllers, chief executives, radiologists, pharmacists, residential advisors, photographers, and members of the clergy.

Still, our researchers caution that it’s early days for AI adoption, and that the impact on jobs will largely depend on how employers ultimately put the technology to best use.

“Until the AI adoption cycle has fully played out, the potential labor market disruption—including which jobs are likely to be displaced by generative AI—will remain an open question,” Briggs and Dong write.

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