Abstract: Artificial intelligence (AI) provides technical support for corporate inventory decision-making. Drawing on a sample of Chinese A-share listed companies from 2010 to 2024, this study applies the BERT language model to conduct an in-depth semantic analysis of corporate annual reports, constructs a firm-level measure of AI adoption, and empirically examines the effect of AI adoption on inventory turnover. The findings indicate that AI adoption significantly improves inventory turnover. Mechanism tests reveal that AI adoption strengthens supply chain coordination and resilience while enhancing the quality of analysts’ earnings forecast, both of which contribute to higher inventory turnover. Extension analyses confirm that the inventory turnover gains driven by AI adoption translate into greater economic benefits. Accordingly, firms should accelerate their digital transformation, strengthen AI innovation and application, and embed inventory turnover into strategic planning over the medium and long term. The government should provide fiscal subsidies and tax reductions or preferences for corporate AI innovation and application, adopt targeted and context-specific policies, and tailor policy support to local conditions so as to promote inventory management optimization and foster a robust industrial ecosystem.

Key words: artificial intelligence applications, supply chain coordination and resilience, earnings forecast quality, inventory turnover rate