Wage Impact — By 2030
Median Wage Impact from AI by 2030
Confidence range: -7% to 1.5%
Real (inflation-adjusted) median wages are projected to fall by 2.5% by 2030 due to AI. This combines two offsetting forces: productivity gains (which push wages up) and displacement of mid-skill tasks (which pushes wages down). The net effect is currently estimated to be negative for the typical worker.
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How This Prediction Has Evolved
Each data point is from a different source. Dots are color-coded by evidence tier.
Sources (16)
Median annual wage for all occupations: $49,500. AI-exposed administrative and clerical wages grew 1.1% vs. 3.8% for non-AI-exposed occupations.
AI-skilled workers command a 56% wage premium, up from 25% in prior year. AI roles median compensation at $157K vs. $49,500 all-occupation median.
Sufficiently advanced AI could dramatically raise growth rates and lower labor share, breaking Kaldor Facts. Wages may rise or fall depending on returns to scale and direction of technical change.
For the empirically plausible case that capital and labor are gross complements, raising wages requires capital-augmenting innovation rather than labor-augmenting.
Walmart raised minimum wage to $15/hr but disclosed AI-driven checkout and inventory systems reducing total store staffing needs by ~8% per location.
Posted wages for AI-exposed occupations (admin, data entry, basic accounting) grew 1.2% YoY vs. 4.1% for non-AI-exposed roles, suggesting wage suppression.
UPS cut 12,000 jobs in 2024 citing AI-optimized routing and automated package sorting. Remaining driver wages increased 2.5% under new contract.
AI exposure is concentrated among high-skill, high-wage occupations, but wage effects may cascade downward.
In most scenarios, AI will likely worsen overall inequality. Higher-income workers may see disproportionate wage gains.
Technology does not automatically benefit workers; shared prosperity requires deliberate policy choices. AI could follow historical pattern of concentrating gains among capital owners.