AI fusion with traditional industries and urban development pathways: evidence from patent-based knowledge recombination in China

Artificial Intelligence (AI) is reshaping New Quality Productive Forces (NQPF) through cross-domain knowledge recombination. However, existing studies rely primarily on aggregate measures such as total factor productivity, limiting their ability to uncover the micro-level mechanisms through which AI drives productivity transformation. Drawing on Chinese patent data from 2000 to 2023 and the standardized technology codes of the International Patent Classification (IPC), this study develops an analytical framework grounded in knowledge recombination to characterize the breadth and depth of AI fusion with traditional industries. Using panel data on 49 Chinese cities and k-means clustering, this paper identifies three distinct development pathways: an "all-round leader" type, which leads across knowledge development, market application, and firm activity; a "market application" type, which advances AI commercialization rapidly on the strength of active firms and rich application scenarios; and a "university-driven" type, in which universities and research institutes dominate knowledge production. This study not only provides a novel measurement approach for capturing how AI reshapes NQPF but also offers an empirical foundation for formulating AI development strategies tailored to local conditions.