AI produces skill compression within firms rather than across sectors, reducing performance gaps among existing workers without addressing inter-sectoral health disparities

Anthropic's synthesis of AI productivity studies reveals a consistent pattern: 'gains appear repeatedly across firms, occupations, and experimental designs and are strongest among initially lower-performing workers, producing skill compression.' This finding is critical for understanding AI's health equity implications. The skill compression is occurring WITHIN firms and occupations — meaning lower-performing customer service representatives catch up to higher-performing ones, or junior programmers narrow the gap with senior ones. However, this within-firm compression does not address the health-relevant disparity between sectors: the gap between high-skill knowledge workers (who benefit from AI) and lower-skill physical laborers (who face chronic disease burden without AI productivity gains). The Anthropic data shows 35.8% observed exposure in computer/math and 34.3% in office/admin, but minimal exposure in construction, manufacturing, and physical services where chronic disease is concentrated. This means AI is compressing skill distributions within the already-advantaged knowledge work sector while leaving the health-burdened physical labor sector untouched, potentially widening rather than narrowing inter-sectoral health disparities.