Research on the Impact of Industrial Intelligence on Labor Employment Structure

Abstract

Based on provincial panel data from 2006 to 2023 in China, this paper systematically investigates the skill stratification effect and regional heterogeneity of industrial intelligence on labor employment structure. It constructs an integrated analytical framework incorporating industrial intelligence level, urbanization, trade openness, industrial structure upgrading, and living costs, employing a fixed-effects model to unravel its mechanisms through three dimensions: substitution effect, creation effect, and productivity effect. The findings reveal that industrial intelligence significantly reduces demand for medium-skilled labor while markedly increasing demand for low-skilled labor, with a relatively modest impact on high-skilled labor. It elevates unemployment rates but concurrently fosters overall employment growth. Regional disparities are pronounced: eastern regions demonstrate positive employment effects from intelligence, whereas central and western regions confront structural unemployment risks due to delayed technological adaptation. Building on these conclusions, the paper proposes establishing a "pyramid-shaped" labor adaptation system, implementing a "flying geese-gradient" intelligent industrialization model, and refining an "incentive-buffer" policy toolkit to address employment challenges during intelligent transformation. Future research should deepen micro-level mechanism analysis, expand cross-national comparative perspectives, and dynamically assess long-term impacts. This study offers new insights into the relationship between technological change and labor markets, providing valuable references for policy formulation and practice.