Tech for Good: The employment effects of policy-driven artificial intelligence development

Employment stability constitutes a fundamental pillar of socioeconomic development, with direct implications for social welfare and societal cohesion. This study utilizes the implementation of Artificial Intelligence Innovation Development Pilot Zones (AIIDPZs) initiated in 2019 as a quasi-natural experiment to investigate how artificial intelligence (AI) development influences corporate employment decisions. Our findings demonstrate that the establishment of AIIDPZs promotes enterprise labor employment, with firms in pilot regions experiencing an average increase in employment scale of approximately 4.56 % compared to enterprises in non-pilot regions, an effect similarly verified at the city level. Mechanism tests reveal that the entrepreneurship incentive effect and the market expansion effect are the operational channels through which AIIDPZs enhance labor employment. Heterogeneity analysis indicates that enterprise-level factors such as company size and ownership structure significantly influence the employment effects of AIIDPZs. Furthermore, industry and regional factors also affect the employment impact of these pilot zones. Further analysis indicates that AIIDPZs increase demand for non-routine, high-skilled, and highly educated labor, reflecting an upgrade in human capital. This research highlights the employment-boosting effects of establishing AIIDPZs, offering valuable policy insights for advancing AI technology applications and achieving stable employment outcomes.

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Publication Details

Journal
International Review of Economics & Finance
Published
2025-12-05
DOI
https://doi.org/10.1016/j.iref.2025.104807
Primary Topic
Digital Economy and Work Transformation
Type
article
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article

Tech for Good: The employment effects of policy-driven artificial intelligence development

Fei Gao, Benhong Peng, Yinyin Zhao, Wei Guo
International Review of Economics & Finance
Digital Economy and Work Transformation
article

Tech for Good: The employment effects of policy-driven artificial intelligence development

Fei Gao, Benhong Peng, Yinyin Zhao, Wei Guo
article en

Abstract

Employment stability constitutes a fundamental pillar of socioeconomic development, with direct implications for social welfare and societal cohesion. This study utilizes the implementation of Artificial Intelligence Innovation Development Pilot Zones (AIIDPZs) initiated in 2019 as a quasi-natural experiment to investigate how artificial intelligence (AI) development influences corporate employment decisions. Our findings demonstrate that the establishment of AIIDPZs promotes enterprise labor employment, with firms in pilot regions experiencing an average increase in employment scale of approximately 4.56 % compared to enterprises in non-pilot regions, an effect similarly verified at the city level. Mechanism tests reveal that the entrepreneurship incentive effect and the market expansion effect are the operational channels through which AIIDPZs enhance labor employment. Heterogeneity analysis indicates that enterprise-level factors such as company size and ownership structure significantly influence the employment effects of AIIDPZs. Furthermore, industry and regional factors also affect the employment impact of these pilot zones. Further analysis indicates that AIIDPZs increase demand for non-routine, high-skilled, and highly educated labor, reflecting an upgrade in human capital. This research highlights the employment-boosting effects of establishing AIIDPZs, offering valuable policy insights for advancing AI technology applications and achieving stable employment outcomes.

International Review of Economics & FinanceVol. 105
Wenzhou University (CN), Nanjing University of Information Science and Technology (CN), University of North Carolina at Pembroke (US), Wenzhou University of Technology
Openalex Percentile: Top 52%
Digital Economy and Work Transformation
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Tech for Good: The employment effects of policy-driven artificial intelligence development — Fei Gao, Benhong Peng, et al. · International Review of Economics & Finance (2025) | TGRS Research Map | TGRS