The impact of artificial intelligence applications on enterprise innovation performance: A case study of the manufacturing industry
Year: 2025
Type: article
Abstract: The application of artificial intelligence (AI) is of significant importance in driving the innovation and development of enterprises. This paper explores how AI applications affect enterprise innovation performance from a micro-level perspective. Based on the Resource-Based View (RBV) and Dynamic Resource-Based View (DRBV), the study empirically tests the impact of AI technology application on the innovation performance of manufacturing enterprises using data from A-share listed manufacturing companies between 2015 and 2023. The research results show that: (1) The application of AI significantly enhances the innovation performance of manufacturing enterprises, and this effect remains significant across various robustness tests. This suggests that the application of AI is a key driver for the efficient utilization of production factors, improving corporate competitiveness and economic growth. Manufacturing enterprises should actively adopt AI technologies to enhance their innovation capabilities and facilitate the conversion of innovation outcomes into economic benefits. (2) Innovation and R&D resources play a significant mediating role in the process by which AI applications enhance innovation performance, with the mediating effect of R&D personnel allocation being the strongest, while the mediating effect of R&D funding allocation is relatively weaker. This finding provides new insights into optimizing the allocation of innovation resources, particularly emphasizing the irreplaceable role of human capital in technological innovation. By optimizing human resource allocation, enterprises can further enhance the marginal benefits of AI applications and promote the continuous development of innovation capabilities. This study provides a theoretical foundation and practical insights for empowering manufacturing industry innovation through AI technology.
Authors: Rongfei Zheng, Chunhui Yuan
Institution: Beijing University of Posts and Telecommunications
Language: English
Topic: Firm Innovation and Growth
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4408631049