Sun Zao, Cao Yuanyuan
Studies of International Finance. 2025, 0(4): 3-14.
With the rapid advancement of the new technological revolution and industrial transformation, artificial intelligence（AI）technology is driving the formation and development of new quality productive forces through revolutionary production methods, becoming a strong support for building a modern industrial system. As a critical engine of contemporary technological revolutions, AI not only enhances production efficiency but also restructures industrial chain layouts. Following the analytical frameworks of Marxist political economy, Schumpeterian innovation theory, and endogenous growth theory, this article analyzes the practical paths of cultivating new quality productive forces and building a modern industrial system through AI, with particularly emphasizing on paradigm-shifting technological breakthroughs.
From the perspective of historical evolution, each industrial revolution has been characterized by transformative technological breakthroughs that catalyze productivity leaps and spur the development of emerging industries. As a key factor input, AI technology facilitates the optimization of production factors by reshaping employment structures and enhancing human capital, while also driving substantial improvements in productivity through knowledge accumulation and R&D innovation. Accordingly, AI technology empowers the transformation of means of production, fundamentally altering traditional production processes and methods. In this regard, AI serves as a powerful driver for the formation of new quality productive forces and the construction of a modern industrial system.
From the perspective of technological innovation diffusion, a defining characteristic of technological transformation lies in product and process innovation. On the one hand, AI enhances new quality productive forces and facilitates the comprehensive upgrading of industrial systems by reducing coordination costs, improving operational efficiency, and optimizing the entire manufacturing process through full-cycle process innovation. On the other hand, AI shortens product development cycles and accelerates knowledge production through predictive analytics and deep learning, thereby enhancing product innovation speed and enabling precise market targeting. Overall, through its internally driven innovation effects, AI serves as a core driving force for fostering new quality productive forces and advancing the modernization of industrial structures by accelerating product innovation and improving the process quality.
From the perspective of industrial system development pathways, new technologies drive the emergence of new sectors and economic growth only when they establish linkages within the industrial chain, facilitating their diffusion into traditional industries and triggering qualitative transformations in productivity. When leading firms adopt AI technology, they exert pressure on upstream suppliers to optimize production processes while fostering increased R&D investment through knowledge spillover effects, thereby enhancing innovation capabilities across the supply chain. Simultaneously, as leading firms leverage AI for intelligent manufacturing and product upgrades, downstream client firms experience peer effects that incentivize them to optimize their existing business models to better align with market demands. Accordingly, AI can drive systematic integration of innovation across the entire industry chain, promote a qualitative leap of productivity, and become a key path to building a modern industrial system.
This article carries profound policy implications. While promoting the development of AI, the government should not only focus on isolated productive applications but also strive to foster the deep integration of AI technology across the entire production sector. Active guidance is needed to encourage the integration of AI technology with traditional manufacturing industries, as well as to foster its innovative development in strategic emerging industries. The implementation of the“AI+”initiative can optimize the combination of production factors and lead the cultivation and development of new quality productive forces. Additionally, there is a need to further improve innovation incentive mechanisms, promoting firms and research institutions to apply AI technology in product design and process simulation. This will enhance product innovation speed and process improvement quality, while also accelerating the transformation and commercialization of technological achievements. Moreover, building an innovation ecosystem that spans across industries and fields is essential, enabling cross-sector and cross-domain collaborative innovation. By establishing a comprehensive innovation ecosystem across the entire industrial chain, new quality productive forces will be fostered, playing a critical role in advancing the construction of a modern industrial system.
