Artificial Intelligence and Labor Income Share: Empirical Evidence from Chinese Listed Companies

Yuting Zhang ()
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Yuting Zhang: Renmin University of China

A chapter in Proceedings of the 2026 11th International Conference on Social Sciences and Economic Development (ICSSED 2026), 2026, pp 214-220 from Springer

Abstract: Abstract While the global labor income share has faced a systemic decline, the impact of Artificial Intelligence (AI) remains a subject of intense debate. This paper utilizes a sample of Chinese A-share listed companies from 2009 to 2022 to empirically examine the relationship between AI application and corporate labor income share. By employing AI-related patent data to measure technological adoption at the micro-enterprise level, the study finds that AI application significantly increases the corporate labor income share. Mechanism analysis reveals that this positive effect is primarily driven by two channels: the mitigation of financing constraints through reduced information asymmetry, and the optimization of human capital structure as firms shift toward high-skilled labor. Further investigation indicates that the promoting effect of AI is more pronounced in non-state-owned enterprises and firms led by executives with digital backgrounds. These findings suggest that AI acts as a productivity-enhancing force that fosters a “human-machine collaborative” model rather than a simple substitution for labor. The study provides a theoretical basis for policies aimed at accelerating digital transformation while ensuring technological dividends are effectively shared with workers.

Keywords: Artificial Intelligence; Labor Income Share; Financing Constraints; Human Capital Structure; Chinese Listed Companies (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6239-701-9_23

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DOI: 10.2991/978-94-6239-701-9_23

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