摘要：绿色生产力以高效能和绿色底蕴赋予了新质生产力形成和发展的质态特征。作为新一轮技术革命的核心驱动，人工智能在提升制造业生产力水平和加速绿色转型方面逐渐展现出巨大潜力。从企业层面出发，通过理论建模与实证分析相结合的方法，系统考察了人工智能技术应用的微观绿色效应。基于2009—2023年中国A股制造业上市公司年报文本及专利等多维指标，构建了企业人工智能技术应用水平的综合测度体系，并从绿色劳动者、绿色劳动对象、绿色劳动资料以及要素组合优化等多个角度对企业绿色生产力水平进行科学评估，以考察二者之间的因果联系。研究发现：人工智能技术应用能够显著提升制造业企业的绿色生产力水平，且这种提升效应具有动态累积性。进一步分析显示，人机匹配度改善与劳动技能结构升级会强化人工智能的绿色生产力提升效应。此外，在异质性方面，人工智能对绿色生产力的促进效果在国有企业、数字化水平较高的企业、实施技术并购的企业以及劳动保障完善的企业样本中更为明显。研究为理解数智化时代下的绿色发展微观机制及新质生产力提升路径提供了参考启示。
关键词：人工智能；绿色生产力；新质生产力；人机匹配；劳动力技能结构
How Does Artificial Intelligence Application Empower the Development of Green Productivity in Manufacturing Enterprises?
Jia Hongye
Abstract: Green productive force endows the formation and development of new-quality productive force with characteristics of high efficiency and a green foundation. As the core driver of the new round of technological revolution, artificial intelligence is gradually demonstrating immense potential in enhancing manufacturing productivity and accelerating the green transition. From the enterprise level, this study systematically examines the micro-level green effects of artificial intelligence technology applications through a combination of theoretical modeling and empirical analysis. Based on multi-dimensional indicators, including annual reports and patents of A-share listed manufacturing companies from 2009 to 2023, we constructed a comprehensive measurement system for the level of AI technology application in enterprises. We then conducted a scientific assessment of corporate green productivity levels from multiple perspectives, including green laborers, green labor objects, green means of production, and the optimization of factor combinations, to examine the causal relationship between the two. The study found that the application of AI technology can significantly enhance the green productive force of manufacturing enterprises, and this enhancement effect exhibits dynamic cumulative properties. Further analysis indicates that improvements in human-machine matching and upgrades in the labor skill structure reinforce the positive impact of AI on green productive force. Additionally, in terms of heterogeneity, the promotional effect of AI on green productive force is more pronounced in state-owned enterprises, enterprises with higher digitalization levels, enterprises that have implemented technology-driven mergers and acquisitions, and enterprises with robust labor protection systems. This study provides valuable insights for understanding the micro-mechanisms of green development and pathways for enhancing new-quality productive force in the era of digital and intelligent transformation.
Keywords: Artificial Intelligence; Green Productive Force; New-Quality Productive Force; Human-Machine Matching; Labor Force Skill Structure
