AI cuts 10,000 roles per month, Pantheon's Tombs and Allen estimate

The two estimates arrive from different directions but point at the same labor-market pattern. Pantheon Macroeconomics' Samuel Tombs and Oliver Allen built their case by tracking job sectors exposed to AI, and the net effect they found is not good: losses above 10,000 roles per month. Goldman Sachs' Joseph Briggs reached a similar conclusion from the productivity side, telling clients that concerns of imminent AI-related job losses have cooled in the media, but recent labor market data show some signs of AI-related hiring headwinds.

The composition matters as much as the total. Construction employment has risen because tech companies are building data centers as fast as they can — a physical buildout that offsets, in part, the slow disappearance of roles in accounting, advertising, office administration and legal services. That split suggests the near-term effect is a reshuffling of where work sits rather than a uniform contraction, though the body offers no figure for how the two sides net out beyond the 10,000-plus monthly losses.

Briggs's framing leaves room for reversibility. His baseline assumes a 15% productivity increase from AI, and under that assumption the roughly 9% of workers affected could be temporarily displaced during the AI transition — a word choice that treats displacement as a phase rather than a permanent endpoint. Whether that holds depends on how the transition unfolds, a question the body raises without resolving.