How artificial intelligence narrows the productivity gap between enterprises: A regional technological spillover perspective

Jiamin Yu (), Sen Yan () and Chuyi Shen ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 3, 228-242

Abstract: This study aims to investigate the mechanisms through which artificial intelligence (AI) contributes to the reduction of productivity disparities among enterprises, specifically through regional technology spillover effects. We constructed a regression model based on the relationship between AI integration and productivity convergence of the listed firms in China from 2001 to 2021. The empirical results, derived from a β-convergence model, reveal a pronounced trend of both absolute and conditional convergence in productivity, signifying that lower-efficiency firms are progressively aligning with their higher-efficiency counterparts. The findings underscore that AI serves as a pivotal driver of productivity enhancement, facilitating not only the catch-up potential of lower-efficiency enterprises but also the speed of productivity convergence across the sector. Our analysis indicates that the deployment of AI significantly elevates production efficiency and fosters overall regional R&D output, thereby creating conducive conditions for mitigating the productivity gap between enterprises. Additionally, the elevation of regional R&D levels further amplifies the growth trajectory of lower productivity firms. The research conclusions of this paper demonstrate the positive significance of applying artificial intelligence in promoting the development of small and medium-sized enterprises.

Keywords: Artificial Intelligence; TFP; Productivity. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://learning-gate.com/index.php/2576-8484/article/view/5183/1905 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:9:y:2025:i:3:p:228-242:id:5183

Access Statistics for this article

More articles in Edelweiss Applied Science and Technology from Learning Gate
Bibliographic data for series maintained by Melissa Fernandes ().