The Stanford Digital Economy Lab's inaugural AI Economic Indicators report, drawing on ADP payroll data covering 4.6 million workers across 25,000 firms, finds that employment in the most AI-exposed occupations is contracting at 3.8% per year for workers aged 22-25 since November 2022, while less-exposed occupations for the same cohort grow at 2.0% per year. Across all age groups the divergence is modest, but the signal sharpens when automation-type AI usage (full task delegation) is isolated versus augmentation-type usage, with automation-heavy occupations showing the clearest employment declines. Separately, the Takeoff Tracker finds that of 12 aggregate macro indicators, seven show no evidence of economic takeoff, three show mild evidence, and two show strong evidence, with TFP growth registering no break from recent trend. For financial institutions, the data provide an early empirical basis for assessing which workforce cost structures and junior hiring pipelines face near-term pressure, and the absence of broad macro takeoff signals constrains productivity-led revenue uplift assumptions in near-term models.
336 other tracked developments touching the same claims.