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The era of AI: Technological change, data protection, and inter-industry wage inequality

Author

Listed:
  • Li, Tailong
  • Shi, Jinmeng

Abstract

This paper develops a theoretical model to analyze how artificial intelligence (AI) reshapes inter-industry wage inequality and how data protection influences the reshape. Moving beyond skill- and task-based models, we conceptualize production as an instruction-based process using machines, data, and labor. By introducing a novel taxonomy of personal- and enterprise-data-intensive sectors, we demonstrate that the ratio of data costs between these sectors is the primary driver of wage inequality, rather than the relative labor supply. This “data cost effect” can explain several puzzling phenomena in the labor market, including the wage divergence among similarly skilled workers and the unexpected resilience of certain low-skill services. Furthermore, we show that stringent data protection and privacy legislation naturally increases the cost of personal data, thereby suppressing wages in sectors that rely on it. Our study establishes a theoretical connection between data governance and wage inequality, offering a new framework for understanding income distribution in the era of AI.

Suggested Citation

  • Li, Tailong & Shi, Jinmeng, 2026. "The era of AI: Technological change, data protection, and inter-industry wage inequality," Socio-Economic Planning Sciences, Elsevier, vol. 104(C).
    • Handle: RePEc:eee:soceps:v:104:y:2026:i:c:s0038012126000066
    DOI: 10.1016/j.seps.2026.102420
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