Wage Impact — By 2030
AI Hub vs. Non-Hub Wage Divergence by 2030
Tech and knowledge workers in AI hub cities (San Francisco, Seattle, New York, Austin) now earn 40.5% more than peers in non-hub metros for comparable roles. This gap has widened dramatically since 2022 as AI investment concentrates geographically. Each AI job in a hub city creates 3-5 additional local service jobs, amplifying the divergence through spatial multiplier effects. Remote work was expected to narrow this gap, but AI talent clustering is widening it.
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How This Prediction Has Evolved
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Additional context
Sources (14)
6.1 million workers in AI-exposed roles lack adaptive capacity; 86% are women. Vulnerability concentrated in college towns and state capitals in Mountain West and Midwest.
Employment 3.6% lower in AI-vulnerable occupations in regions with high AI-skill demand after 5 years; geographic divergence driven by skill concentration.
Mountain region leads US AI adoption at 42%, followed by Pacific at 39%. Southeast lags at 22%. Regional adoption gaps correlate with widening wage divergence.
AI roles median salary $157K in hub metros vs. $49,500 median for all occupations nationally. Geographic premium for AI talent continues to widen.
AI usage heavily concentrated by income and geography globally; within US, workforce composition matters more than income for adoption patterns.
Computer and mathematical occupations in San Jose-SF-Oakland MSA: $178K median. National median: $108K. Gap up from 48% to 65% since 2022.
43% of workers in San Jose could see AI shift half or more of tasks, vs only 31% in Las Vegas. High-skill metro areas most exposed — reversing prior automation patterns.
Median AI/ML salary in San Francisco reached $245K. In non-hub metros, AI salaries average $162K. The 50% gap is the widest in tech history.
Each AI job in a hub city creates 3-5 local service jobs. Non-hub cities see net job losses. The spatial multiplier amplifies geographic wage divergence.
AI adoption is concentrating economic gains in a handful of superstar cities, widening the already large metro-level wage divergence.
AI engineer median salary in San Francisco: $225K. Same role in Kansas City: $155K. Gap widening as demand concentrates.
60% of AI/ML job postings concentrate in 10 metro areas. AI roles in SF/Bay Area pay 35% more than identical roles in mid-tier cities.