Artificial Intelligence Drives Down Pay for Millions of Workers

2026-08-02 economy

New York, Saturday, 1 August 2026.
Recent data reveals artificial intelligence is suppressing real wages in exposed roles by 6.7% rather than causing mass layoffs, quietly altering white-collar earning potential.

Wage Compression in High-Exposure Sectors

A whitepaper published by Apollo Global Management on July 30, 2026, indicates that artificial intelligence adoption is correlating with suppressed real wage growth rather than immediate mass layoffs [1][3]. Roles with high exposure to AI integration experienced an average 6.7% decline in real wage growth post-2023, affecting approximately 5.8 million workers across the United States [1][3]. The impact is disproportionately felt by lower-income earners, with service workers seeing a 24.3% decline in earnings growth and the bottom 25% of earners facing a 10.7% wage decline since 2023 [1]. Economists Sania Edlich and Torsten Slok note that as AI adoption deepens across corporate America, the number of workers feeling these effects is likely to grow substantially, carrying significant implications for income inequality [1][3]. While some specific occupations with high AI-task exposure saw wage growth, such as personal finance advisors at 8.4%, the broader trend indicates a compression of compensation benchmarks in administrative and technical sectors [1]. The report estimates that affected workers lost $28 billion annually, highlighting a shift where productivity gains from automated technologies are not being passed down to labor compensation [3].

Labor Demand and Employment Stability

Contrary to fears of widespread displacement, employment levels in AI-exposed occupations have remained relatively unchanged, suggesting companies are capturing productivity gains through wage compression rather than workforce reduction [2][6]. Research from the Federal Reserve Bank of New York released in May 2026 analyzed job-posting data and found little indication of a distinct AI-driven decline in labor demand following the release of ChatGPT in late 2022 [6]. Firms in the Second District are more likely to retrain workers in AI-exposed roles than to reduce hiring, mitigating the potential for increased layoffs [6]. However, a Harvard Business School working paper from December 2024 identifies a heterogeneous impact, where generative AI-driven automation reduces labor demand by 17% per quarter per firm in structured cognitive-task jobs while increasing demand by 22% in roles involving human-AI collaboration [8]. This divergence suggests that while overall employment may remain stable, the nature of work and required skills are shifting rapidly, with AI-exposed skills decreasing by 24% in automation-prone jobs and increasing by 15% in augmentation-prone roles [8].

Macroeconomic Scenarios and Fiscal Risks

The broader economic implications extend to fiscal stability, with the New York City Comptroller’s office modeling several AI-impact scenarios through 2030 [7]. In an “AI Shockwave” scenario, which carries a 5% probability, the U.S. could lose 5.4 million private sector jobs through mid-2028, resulting in a cumulative tax revenue shortfall of roughly $14 billion for New York City through fiscal year 2030 [7]. Conversely, a “Productivity Boon” scenario projects U.S. real GDP growth of 2.9% annually, though this remains the most optimistic outlook [7]. Investment expectations for digital infrastructure to support AI deployment total $4 trillion to $5 trillion by 2030, requiring annual AI revenue to reach $1.5 trillion to $2 trillion to achieve acceptable returns [4]. With consumer spending growing faster than income in July 2026 and personal savings declining, the tension between infrastructure investment and labor income suppression presents a complex challenge for policymakers evaluating capital allocation and labor strategies [3][4].

Sources

Artificial Intelligence Wage Growth