关键词: 产融合作, 人工智能应用, 专项融资, 资源配置, 数据资产化

Abstract: In the context of the 15th Five-Year Plan driving the AI+ Initiative to empower the real economy, tackling financing difficulties and high costs in corporate AI adoption is an urgent imperative. This study takes the 2016 pilot policy of industry-finance cooperation as a quasi-natural experiment. Based on data of A-share listed companies from 2011 to 2023, it employs the difference-in-differences (DID) model to examine the policy's impact on corporate AI applications and its underlying mechanisms. The results indicate that the industry-finance cooperation policy significantly promotes corporate AI applications, and this conclusion remains robust after a series of robustness tests including the staggered DID model. Mechanism analysis shows that the policy exerts its effect through three pathways: improving access to dedicated financing for AI projects, enhancing the calibration of resource misallocation, and advancing the assetization of data factors. Furthermore, the driving effect is more pronounced in enterprises with executives having high-tech backgrounds, enterprises with weak governance, enterprises with low institutional ownership, high-tech enterprises, and regions with a high level of digital economy development. From the perspective of resource orchestration, this study reveals the resource integration value of the industry-finance cooperation pilot, providing a theoretical basis and targeted plans for optimizing policy tools that enable AI to empower the real economy.

Key words: Industry-Finance Cooperation, Corporate AI Applications, Dedicated Financing, Resource Allocation, Data Assetization