AI pilot zones and corporate investment efficiency under monetary policy uncertainty: evidence from China

This paper examines whether a place-based artificial intelligence policy improves corporate investment efficiency and whether its effect varies with monetary policy uncertainty and firms’ financial vulnerability. Exploiting the phased rollout of China’s National New Generation Artificial Intelligence Innovation and Development Pilot Zones, we employ a staggered difference-in-differences approach for a panel of Chinese A-share listed firms from 2015 to 2023. We find that the AI pilot-zone policy significantly reduces investment inefficiency, and the reduction is more pronounced among firms with greater short-term refinancing exposure or tighter financing constraints when monetary policy uncertainty is elevated. Using 6.93 million online job postings classified with a fine-tuned MacBERT model, we further show that the policy shifts the composition of AI recruitment towards finance-related vacancies, while overall postings decline. These findings extend evidence on place-based AI policy to corporate capital allocation and highlight the role of financial information-processing capacity in shaping investment efficiency under monetary policy uncertainty.