Purpose: This research aims to investigate the impact of artificial intelligence (AI) adoption on the innovation dynamics of Chinese manufacturing enterprises, with a specific focus on the intricate interplay with the labor structure.Design/methodology/approach: Leveraging panel data of listed companies from 2010 to 2022, this study employs the two-way fixed effects (TWFE) model to examine the influence of AI adoption on Chinese manufacturing companies' innovativeness. Firm-level AI adoption is measured by constructing a three-dimensional attention, application and absorption index.Findings: The results indicate that (1) AI adoption has a positive impact on both internal innovation capability and external innovation interaction, (2) AI adoption has dual effects on the education and skill structure of labor in manufacturing enterprises and (3) enterprises with a highly educated and skilled workforce exhibit a stronger influence of AI adoption on innovativeness.Originality/value: This research contributes to the academic and practical discourse by unveiling the underlying mechanisms of AI affecting innovation and introducing a new measurement of the AI adoption index. The findings emphasize the need for a highly educated and skilled workforce to navigate the complexities of AI-driven innovation, offering valuable theoretical and practical implications for policymakers and enterprises.

China, at the forefront of carbon emissions and manufacturing, grapples with substantial challenges in harmonizing economic progress and environmental protection (EP). This study delves into the intricate interplay between carbon footprint methodologies (CFM), sustainable product development (SPD), EP, and the moderating role of regulatory compliance. To fulfill its objectives, the research meticulously analyzes data collected from a sample of 429 employees within the manufacturing sector, employing SmartPLS version 4.1. The results reveal a noteworthy impact of CFM on both SPD and EP. Additionally, SPD demonstrates a positive effect on EP. Furthermore, the study uncovers SPD as a significant mediator in the association between CFM and EP. Finally, regulatory compliance moderates CFM–EP correlation. These findings underscore the critical interconnectedness of CFM, SPD, and regulatory compliance in fostering a more environmentally conscious manufacturing sector in China, offering valuable insights for academia, businesses, and policymakers.