Amidst the tremendous evolution of the digital economy and the expedited establishment of a new development paradigm, the use of artificial intelligence (AI) technologies holds significant importance in achieving superior economic development. While much of the previous research focused on the macroeconomic impact of AI, this study examined how AI technology affects food processing firm performance, productivity, and labor skill structure at the food processing firm level. This study utilized panel data from listed food processing enterprises in Shanghai and Shenzhen spanning from 2010 to 2021, performing textual analysis on the annual reports of listed companies and then creating enterprise-level AI indicators to empirically examine the influence of AI applications on enterprise performance and its underlying mechanisms. The findings indicate a substantial improvement in business performance due to the application of artificial intelligence, which is a conclusion corroborated through a series of stability tests. Exploring channels and mechanisms, the analysis revealed that AI-driven advancements in production technologies stimulated the requirement for highly skilled labor, thereby inducing shifts in the labor force’s structure. Further investigation demonstrated that artificial intelligence contributed to enhancing the total factor productivity, consequently bolstering the overall enterprise performance. A heterogeneity analysis showed that firm-level factors, such as the nature of property rights and factor intensity, had an impact on the influence of AI on firm performance. In addition, the geographic location and time of year of a company also had impacts on the productivity benefits of artificial intelligence. This research deepened the cognition and understanding of the role played by AI in the production process at the micro-enterprise level and provided suggestions for promoting the development of artificial intelligence technologies at the micro-enterprise level, which will facilitate the transformation of the labor structure to further augment enterprise efficiency.

Accelerating the green development of the dairy industry is an important work to promote the construction of ecological civilization and ensure the safe supply of dairy products. Existing studies lack a comprehensive analysis of the green development characteristics of China’s dairy industry. Based on the input–output system, the study measured and analyzed the green total factor productivity of China’s dairy industry in 29 provinces (cities, autonomous regions, and municipalities) since the 10th Five-Year Plan period, using the super-efficiency EBM model and the GML index based on non-directional and variable scale returns. Accelerating the green development of the dairy industry is an important work to promote the construction of ecological civilization and ensure the national nutrition intake. The existing studies lack a comprehensive understanding of the green development characteristics of China’s dairy industry. Therefore, this paper constructs an input–output system, measures and analyzes the green total factor productivity of the dairy industry in 29 provinces (cities, autonomous regions and municipalities directly under the Central Government), since the “15th Five-Year Plan” period based on the non-oriented super-efficiency EBM model and GML index with variable returns to scale. On this basis, the dynamic evolution of regional differences was explored using Kernel density estimation and the Dagum Gini coefficient, and the influencing factors of green total factor productivity in China’s dairy industry were analyzed using a two-way fixed effects model. The results show that from 2001 to 2020, the green total factor productivity of China’s dairy industry showed an overall upward trend, and presented a gradient pattern of “Northeast–East–Central–West” in turn, with green technical efficiency being the main driving force for promoting green total factor productivity in China and various regions. The gap in green total factor productivity between provinces and cities is gradually narrowing, and the polarization phenomenon is weakening. Super variation density is the main source of regional differences, and the difference between the West and the East is the largest, while the difference between the Central and the Northeast is the smallest. As for the influencing factors, industry agglomeration, economic development level, and environmental planning level have a significant positive promoting effect on the green total factor productivity of China’s dairy industry, while the level of population urbanization has a significant inhibitory effect on it. In order to promote the green and sustainable development of China’s dairy industry and promote the coordinated development of regional green, it is necessary to accelerate the efficiency of green technology while promoting the innovation of green technology, accelerate the integrated development of industry and formulate relevant policies according to local conditions to promote the coordinated development of green technology between regions.