Goldman's Briggs: AI could displace 9% of workers, but layoffs wait for recession

Goldman Sachs has now made a version of this argument twice in a year from two different teams. In October 2025, U.S. economists David Mericle and Pierfrancesco Mei described "jobless growth" as the likely new normal and warned that AI's full labor-market consequences might not become apparent until a recession hits. Briggs reaches the same conclusion through a different route: decades of data showing that companies tend to automate work and shed labor costs when the economy starts to slow.

The historical record Briggs cites is stark. The share of Americans in routine jobs — clerks, secretaries, factory machine operators, mechanics — has dropped in steps at the early 1980s, 2001, 2008 and 2020 recessions and never returned to prior levels. Across 25 occupations that past technology upended, employment fell an extra 4% over five years for every point the national unemployment rate climbed. Briggs calls those cases "likely upper bounds" for AI because he selected the hardest-hit examples.

That framing helps explain why the current moment looks calm. AI-attributed layoffs in Challenger's tracking have pulled back sharply from their spring peak, and job growth in the most AI-exposed industries has run about 10,000 below its long-run trend over the past three months, roughly offset by hiring for AI-related construction. Briggs also lists reasons his 9% could prove low: displacement ran higher during the late-1990s/early-2000s productivity boom, the period most widely viewed as comparable to today, and higher after unusually large productivity jumps — which Goldman expects AI's boost to beat.