Briggs’s estimate rests on Goldman’s forecast that AI will eventually raise productivity by 15 percent in the US and other developed economies. On that assumption, up to 9 percent of workers could be displaced during the AI transition, or roughly one in 11. Slower hiring could weigh on employment by a further 3 percent.
Artificial intelligence has been at the centre of workforce disruption debates for the past two years, but according to a new analysis from Joseph Briggs, an economist at Goldman Sachs, the biggest impact on jobs may not arrive immediately. Instead, large-scale AI-driven layoffs could accelerate during an economic downturn, even as the current labour market remains relatively resilient.
The latest analysis echoes warnings issued by Goldman Sachs economists David Mericle and Pierfrancesco Mei in October 2025. Briggs noted that only 23% of US establishments have incorporated AI into regular workflows, meaning most productivity gains expected from the technology still lie ahead. The economist also pointed to a resilient labour market in 2026.
Because economic conditions have remained relatively stable, he argued that companies currently have less incentive to aggressively cut jobs.
At the time, they argued that “jobless growth” could become a recurring feature of the economy, where GDP continues to grow but employment expands more slowly. The timing and extent of AI-driven job disruption will likely track broader economic cycles rather than occurring in a sudden wave, according to Briggs. One reason widespread AI-related layoffs have not yet materialised is that adoption remains at an early stage, according to the report.
The pair also suggested that the full impact of AI on employment might not become apparent until a recession occurs, allowing companies to restructure workforces more aggressively while implementing automation. Recent indicators cited in the report suggest only modest labour-market effects so far.
“Automation-related labour disruption is limited when the overall economy is healthy but accelerates during cyclical slowdowns,” he wrote, according to the Fortune report. The report’s central argument is that AI’s impact on employment is likely to follow a familiar historical pattern. After examining decades of data on technological change and labour markets, Briggs concluded that automation tends to accelerate during economic slowdowns rather than periods of strong growth.