A new study spanning multiple universities has challenged previous economic assumptions about artificial intelligence’s labor market impact, with 69 economists, 52 AI experts, and 38 superforecasters now agreeing that faster AI adoption will lead to significant job displacement. The research, conducted across MIT, Stanford, and Cambridge economics departments, marks a notable reversal from earlier predictions that AI would primarily augment rather than replace human workers.
The study’s longitudinal analysis tracked three distinct cohorts from 2022-2026, revealing a dramatic shift in expert opinion as real-world AI implementation accelerated. Where 72% of participating economists originally predicted net job creation through 2030, that figure dropped to 31% in the latest survey round. Productivity gains from generative AI tools were found to disproportionately benefit capital over labor, particularly in knowledge sectors previously considered automation-resistant.
“We’re seeing productivity spikes in AI-adopting firms that aren’t translating to proportional wage growth or hiring,” noted one labor economist involved in the study who requested anonymity due to unpublished parallel research. Treasury Department officials confirmed they’re monitoring the trend but declined to comment on potential policy responses.
Industry analysts suggest the findings may accelerate calls for revised workforce training programs and safety net expansions. With AI adoption rates exceeding even bullish 2023 projections, the study’s authors warn conventional economic models may need fundamental recalibration for what they term “the second half of the chessboard” of technological disruption.