AI and Labor Market Outcomes: Evidence from China

Tony Fang (), Carl Lin () and Qing Liu ()
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Tony Fang: Memorial University of Newfoundland, NL, Canada
Carl Lin: Bucknell University Lewisburg, PA, USA
Qing Liu: Hefei University of Technology, Anhui, China

No 18740, IZA Discussion Papers from IZA Network @ LISER

Abstract: We construct city–year measures of AI labor demand from 1.6 million online job postings between 2016 and 2024, and merge them with nationally representative microdata from the China Family Panel Studies (2016–2022). Fixed-effects estimates show that local AI labor demand has positive impacts on individual wages: a one-unit increase in AI demand (1,000 postings, firms, or job titles) raises wages by about 0.2–0.3 percent. Women experience stronger gains—about 0.5–0.7 percent per unit increase—while men show no measurable effect. Wage effects are largest in Western provinces, and in China’s major AI-cluster cities where complementary production factors and digital infrastructure are most developed. Occupational analyses further show that women’s gains are concentrated in service-oriented, less skill-intensive jobs where AI complements interpersonal and coordination tasks rather than substituting them. Overall, AI diffusion generates meaningful but unequal labor market spillovers, with wage gains concentrated among women, dynamic regions, and human–AI complementary occupations, underscoring both the opportunities of technological transformation and the challenges of achieving inclusive growth.

Keywords: artificial intelligence (AI); labor market; wages; productivity; China (search for similar items in EconPapers)
JEL-codes: I23 J24 (search for similar items in EconPapers)
Date: 2026-06
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