Recently, the paper titled “Artificial Intelligence, Occupational Skill Structure and Industrial Structural Transformation”, co-authored by Dr. HU Lianyi from the Department of Economics of the School, Associate Research Fellow PAN Shan from Jinan University and Professor GAI Qing'en from Shanghai Jiao Tong University, was published in Management World, a top-tier journal in the field of management. Dr. HU Lianyi serves as the corresponding author of this paper.
The widespread application of artificial intelligence (AI) technology has not only triggered the transformation of the labor occupational skill structure at the micro level, but also driven industrial structural transformation at the macro level. Based on presenting the stylized facts of changes in China’s industrial-level occupational skill structure, this paper constructs a multi-sector general equilibrium model that incorporates AI technology and occupational skill heterogeneity, and conducts qualitative and quantitative analyses of the impact of AI technological development on occupational skill structure and industrial structural transformation. The paper draws the following findings: First, if AI technology exerts biased impacts on different skills, the advancement of AI technology will drive industrial structural transformation and the transformation of occupational skill structure within industries – specifically, the employment share of routine occupational skills declines, that of social occupational skills rises, and the employment share of cognitive occupational skills depends on the relative magnitude of AI’s bias toward different occupational skills. Second, from the perspective of the effect decomposition of changes in occupational skill shares, the intensive margin effect within the service industry and the extensive margin effect of industrial structural transformation account for a relatively high proportion of the total effect. Third, the results of numerical simulation show that as AI technology upgrades at an accelerated pace and its impacts on different occupational skills converge, it will ultimately slow down the decline in the employment share of routine occupational skills, drive the share of cognitive occupational skills to shift from rising to falling, and sustain the increase in the share of social occupational skills. In other words, the upgrading of AI technology is mainly reflected in the "crowding-out" effect on cognitive occupational skills. From an industrial perspective, this paper expounds on the impact of AI on occupational skill structure and industrial structural transformation, quantitatively evaluates the future development trends, and provides policy references for the transformation and reform of the labor market under the impact of AI.
Dr. HU Lianyi graduated from Shanghai Jiao Tong University and joined the School in 2025, and was selected for the Shanghai Pujiang Talent Program. Her research focuses on labor economics and development economics. She has published a number of papers as the first author or corresponding author in various authoritative domestic and international journals including Economic Research Journal, Management World, China Industrial Economics and the Journal of Population Economics.
Paper information: PAN Shan, GAI Qing'en, HU Lianyi. (2026). Artificial Intelligence, Occupational Skill Structure and Industrial Structural Transformation. Management World, 43(2), 107-124.