Can artificial intelligence applications enhance innovation efficiency in private enterprises: evidence from China

Based on a systematic review of the current state of artificial intelligence (AI) applications in China, we construct a Double Machine Learning (DML) model to empirically examine whether AI applications enhance the innovation efficiency (IE) of private enterprises (PEs), using data from 829 Chinese PEs between 2010 and 2023. The results reveal that AI significantly enhances IE in PEs. Specifically, at the innovation input stage, AI adoption significantly increases the number of R&D personnel, while at the innovation output stage, it significantly promotes both substantive innovation and strategic innovation. This process relies heavily on strengthening the resilience of private-sector supply chains. Moreover, the innovation-enabling effect of AI is more pronounced in technology-intensive and capital-intensive PEs than in their labour-intensive counterparts. In addition, we find that AI not only enhances the IE of PEs but also improves their average and overall innovation quality, thereby achieving ‘both quality and efficiency’. Based on the conclusions and case discussions, we have distilled a ‘technology-sharing-value’ pathway for enhancing the IE of PEs. These findings enrich the existing literature and offer practical implications for PEs in emerging markets to optimise AI strategies and design more targeted application plans.