Research on New Generation Artificial Intelligence Driving Deep Industrial Transformation and Upgrading — From the Perspective of Production Function Transformation and Factor Collaborative Matching

Authors

  • CAO Yuping School of Economics, Henan University, Kaifeng 475000, China
  • LIU Jingwei School of Economics, Henan University, Kaifeng 475000, China
  • ZHENG Zhanpeng School of Economics, Henan University, Kaifeng 475000, China

DOI:

https://doi.org/10.20069/5wywhj66

Keywords:

new generation artificial intelligence, industrial transformation and upgrading, general-purpose meta-technology, production function transformation, factor collaborative matching, new quality productive forces, intelligent economy

Abstract

Deep industrial transformation and upgrading not only balances rapid economic growth with high-efficiency development but also ensures economic sustainability and industrial security. As a typical representative and important source of new quality productive forces, new generation artificial intelligence (AI) possesses powerful potential to catalyze the fourth industrial revolution. Accelerating the research, development and industrial application of new generation AI is both an important strategic deployment to promote China’s leapfrog technological development and overall productivity enhancement. Against this backdrop, and an inevitable path to seize opportunities in industrial transformation. Against this backdrop, there is an urgent need to systematically study the intrinsic mechanisms by which new generation AI drives China’s deep industrial transformation and upgrading, and to comprehensively identify prominent challenges and countermeasures in this process.

Based on a comprehensive understanding of the general-purpose meta-technological characteristics of new generation AI, this paper adopts two complementary analytical perspectives. First, from the perspective of production function transformation, it systematically explains how AI reshapes input factors, functional relationships, and output paths in the modern economic growth equation, thereby driving the systematic optimization and restructuring of traditional industries. Second, from the perspective of factor collaborative matching, it reveals in depth the theoretical mechanisms through which AI promotes the comprehensive construction of a modern industrial system—by forming new patterns of human-machine division of labor, mitigating information asymmetry, achieving efficient separating equilibria, and reducing search and matching costs.

Although new generation AI has powerful theoretical potential to drive deep industrial transformation and upgrading, it faces numerous obstacles in practice. This paper further identifies prominent issues in the processes of intelligent industrialization and industrial intelligence from five dimensions—micro, meso, macro, international, and future-oriented—and proposes corresponding countermeasures: creating a micro-level ecosystem conducive to creative destruction in intelligent transformation; promoting coordinated and balanced development of the intelligent economy at the meso level; establishing an excellent development environment for new quality productive forces at the macro level; building an autonomous and controllable core technology system in the international environment; and proactively planning the direction of intelligent transformation from a future perspective.

This paper makes three main marginal contributions: First, it comprehensively reviews the novel techno-economic characteristics of new generation AI, establishing a cognitive foundation for explaining its effects on deep industrial transformation. Second, based on the perspectives of production function transformation and factor collaborative matching, it constructs a theoretical framework for new generation AI driving traditional industrial optimization and restructuring, as well as modern industrial system construction. Third, it systematically identifies prominent issues in new generation AI driving China’s deep industrial transformation and upgrading, and proposes targeted countermeasures.

Through characteristic recognition, theoretical exposition, pain point identification, and countermeasure proposal, this paper provides a theoretical analytical framework and practical response measures for deeply understanding the new driving force and creative destruction effects of new generation AI in China’s deep industrial transformation and upgrading. It has important implications for China to seize opportunities in disruptive technological change, innovate industrial development ecosystems, and construct a modernized industrial system.

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Published

2025-08-16

How to Cite

Research on New Generation Artificial Intelligence Driving Deep Industrial Transformation and Upgrading — From the Perspective of Production Function Transformation and Factor Collaborative Matching. (2025). Modern Economic Science, 47(4), 80-96. https://doi.org/10.20069/5wywhj66

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