The Spillover Effects of Peer AI Rinsing on Corporate Green Innovation

A new research paper titled 'The Spillover Effects of Peer AI Rinsing on Corporate Green Innovation' provides the first large-scale empirical evidence that corporate 'AI washing' actively harms sustainable innovation. The study, authored by Li Wenxiu, Wen Zhanjie, Xia Jiechang, and Guo Jingqiao, used large language models (LLMs) to perform semantic analysis on annual reports from Chinese A-share listed companies spanning 2006 to 2024. Their analysis systematically identifies companies that use AI terminology as 'cosmetic embellishment' rather than for genuine transformation, revealing this practice creates a significant crowding-out effect on green innovation.

The research identifies dual transmission channels for this negative impact: in product markets, resources are diverted from real R&D to marketing hype, and in capital markets, misled investment flows away from sustainable projects. The damage is not uniform; private enterprises, small and medium-sized enterprises (SMEs), and firms in highly competitive sectors suffer the most severe consequences. Using agent-based modelling simulations, the authors found that a combination of policy interventions could improve market equilibrium. They propose a regulatory framework featuring targeted support tools to 'enhance market returns and alleviate financing constraints' for genuine innovators, alongside a disclosure mechanism combining professional verification with reputational sanctions to deter AI washing.