Enterprise AI Analysis

Empowering New Quality Productive Forces through Artificial Intelligence Technology: A Study on the Pathways and Threshold Effects in High-Quality Development of Manufacturing Industry

Authors: Jingzhou Zhao, Yu Hu, Wei Deng, Wenxiao Duan, Xiaokang Chang, Junru Zhou

Publication: 2025 International Conference on Artificial Intelligence and Computational Intelligence (AICI 2025), Kuala Lumpur, Malaysia (February 14-16, 2025)

This paper first conducts a regression analysis on the direct effect of artificial intelligence on the high-quality development of the manufacturing industry, and then uses the panel threshold model to explore the threshold effect of artificial intelligence on the high-quality development of the manufacturing industry. The Hausman test confirms the rationality of the fixed effect regression model, indicating that artificial intelligence has a significant positive impact on the high-quality development of the manufacturing industry. Subsequently, the panel threshold model is used for analysis, and it is found that there is a double threshold effect, with the first threshold value being 6.5575 and the second being 14.4800. The marginal effect of the improvement of artificial intelligence level on high-quality development shows a rapid increase at first, a slowdown after crossing the first threshold, and an acceleration again after crossing the second threshold. This nonlinear relationship is further verified through the adjustment ratio change and internal validity test for robustness. The results show that high-end and low-end manufacturing enterprises are more likely to benefit from artificial intelligence technology due to advantages in cost-effectiveness, market demand, and technological adaptability, thereby promoting their high-quality development. In contrast, mid-range manufacturing enterprises may face a series of challenges, resulting in less significant or even inhibitory effects of artificial intelligence technology on them.