新一轮科技革命加速演进背景下，人工智能作为新型劳动工具的典型代表，符合新质生产力发展要求。分析人工智能影响新质生产力的理论机制，并基于2010—2022年中国内地30个省份面板数据和国际机器人联合会（IFR）的工业机器人数据，利用双向固定模型和工具变量法进行实证检验。研究发现：人工智能发展能够显著促进新质生产力提升，并且这一结论经过一系列稳健性检验和内生性检验后依然成立。机制分析发现，人工智能主要通过增强创新能力、改善能源效率和提高数字化水平3个渠道促进新质生产力提升。异质性分析发现，人工智能对新质生产力的带动效应在市场化程度高、技术聚集程度高和产业结构优化水平高的地区更显著。最后，针对发展人工智能、促进新质生产力发展提出对策建议：完善市场经济基础制度，创设有利于人工智能企业发展的营商环境；加快发展人工智能技术，持续推动产业结构优化升级；搭建人工智能创新应用场景，加大人工智能技术推广应用力度。

New quality productive forces refer to modern advanced productive forces that have been created through revolutionary technological breakthroughs, innovative allocation of production factors, and deep transformation and upgrading of industries, the core essence of which is the qualitative transformation of the three elements of workers,means of labor, and labor objects and their optimal combination, and the most significant symbol of which is a significant increase in total factor productivity. It significantly differs from the traditional productivity of high input and high energy consumption, emphasizes key and disruptive technological breakthroughs, and is characterized by high technology, high efficiency and high quality. New quality productive forces bring about a qualitative leap in productivity and serve as the driving force for facilitating high-quality development in the new era. The development of artificial intelligence (AI) provides new ideas and new impetus for fostering new quality productive forces and promoting high-quality development. AI's ongoing development will drive technological innovation, increase production intelligence, spawn new economic sectors, and integrate with traditional industries to enhance resource allocation efficiency and labor productivity. This integration will steer traditional production models towards greater scalability and specialization, moving industries up the value chain.
The examination of artificial intelligence's influence on new quality productive forces holds substantial theoretical and practical importance. The literature review indicates that existing studies predominantly concentrate on the essence, value, and developmental priorities of new quality productivity, as well as AI's effects on productivity, economic growth, employment, and industrial structure. However, there is a scarcity of research addressing the nexus between AI and new quality productive forces, and empirical evidence on AI's role in shaping these forces is limited. The reasons and mechanisms by which AI bolsters new quality productive forces are not well understood.
This paper aims to bridge this gap by theoretically and empirically analyzing AI's impact on new quality productive forces using provincial panel data, revealing the underlying mechanisms and regional disparities in AI's promotion of new quality productive forces, thereby enriching and advancing the discourse on AI and new quality productive forces. This study focuses on 30 provincial administrative regions in China. Data limitations preclude the inclusion of Hong Kong, Macao, and Taiwan, while Xizang is omitted due to incomplete data records. To ensure data consistency and completeness, linear interpolation is applied to estimate missing values in certain provinces; any unfillable gaps are addressed by listwise deletion, ensuring the reliability of the analysis.
The findings suggest that the development of AI can significantly contribute to the improvement of new quality productive forces. The robustness of the findings of this study is verified by conducting robustness tests,shortening the sample period, replacing the explanatory variable, adding control variables, and removing extreme values. In addition, the study employs the number of robots installed in the U.S. as the instrument variable to address potential endogeneity issues in the model and ensure that the estimates are unbiased. Through mechanism analysis, it reveals that AI contributes to new quality productive forces through three main channels: improving innovation, improving energy efficiency, and improving digitization. Through heterogeneity analysis, the study further finds that the driving effect of AI on new quality productive forces is more significant in regions with high marketization, high technology aggregation, and high industrial structure optimization.
This paper deepens the theoretical mechanisms by which AI promotes new quality productive forces on the basis of the existing literature and provides strong empirical evidence for the new quality productive forces effect of AI through empirical tests. Further, this study explores the fundamental question of the path through which AI mainly affects new quality productive forces within a unified framework, supporting the role of innovation capacity, energy efficiency, and digitization level in the path through which AI affects new quality productive forces, and deepens the existing literature and related studies. In accordance with the findings of the study, the paper puts forward policy recommendations conducive to the full development of AI and the promotion of new quality productive forces, which will provide important decision-making references for the development of new quality productive forces in various regions according to local conditions.