At a time when the phenomenon of 'AI washing' is quietly spreading, an increasing number of enterprises are using the label of artificial intelligence merely as a cosmetic embellishment in their annual reports, rather than as a genuine engine driving transformation. A test regarding the essence of innovation and the authenticity of information disclosure has arrived. This paper employs large language models to conduct semantic analysis on the text of annual reports from Chinese A-share listed companies from 2006 to 2024, systematically examining the impact of corporate AI washing behaviour on their green innovation. The research reveals that corporate AI washing exerts a significant crowding-out effect on green innovation, with this negative relationship transmitted through dual channels in both product and capital markets. Furthermore, this crowding-out effect exhibits heterogeneity across firms and industries, with private enterprises, small and medium-sized enterprises (SMEs), and firms in highly competitive sectors suffering more severe negative impacts from AI washing. Simulation results indicate that a combination of policy tools can effectively improve market equilibrium. Based on this, this paper proposes that the government should design targeted support tools to 'enhance market returns and alleviate financing constraints', adopt a differentiated regulatory strategy, and establish a disclosure mechanism combining 'professional identification and reputational sanctions' to curb such peer AI washing behaviour.

翻译：在"AI粉饰"现象悄然蔓延的当下，越来越多企业将人工智能标签仅作为年报中的修饰性点缀，而非驱动转型的真正引擎。关于创新本质与信息披露真实性的考验已然到来。本文运用大语言模型对2006-2024年中国A股上市公司年报文本进行语义分析，系统考察企业AI粉饰行为对其绿色创新的影响。研究表明，企业AI粉饰对绿色创新存在显著的挤出效应，这一负向关系通过产品市场与资本市场的双重渠道传导。此外，该挤出效应呈现企业与行业异质性，民营企业、中小企业及高竞争行业企业受AI粉饰的负面冲击更为严重。模拟结果表明，政策工具组合能够有效改善市场均衡。据此，本文建议政府应设计"提升市场收益与缓解融资约束"的定向支持工具，采取差异化监管策略，并建立"专业识别与声誉惩戒"相结合的信息披露机制，以遏制此类同行AI粉饰行为。