AI-Generated Content and ESG: A Quasi-Natural Experiment based on CHATGPT

Li Chai (), Li Qiao (), Tianying Sun (), Yunxuan Zhu () and Aoling Hou
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Li Chai: School of International Trade and Economics, Xinjiang University of Finance and Economics, No. 449, Beijing Middle Road, High-tech Development Zone (New District), Urumqi City, Xinjiang Uygur Autonomous Region, China, 830063.
Li Qiao: Corresponding Author, School of Business, Beijing Union University, No. 3A, Yanjing Dongli, Chaoyang District, Beijing Municipality, China, 100025.
Tianying Sun: School of International Trade and Economics, Central University of Finance and Economics, No. 39, South College Road, Haidian District, Beijing, China, 100081.
Yunxuan Zhu: School of International Trade and Economics, Central University of Finance and Economics, No. 39, South College Road, Haidian District, Beijing, China, 100081.
Aoling Hou: School of International Trade and Economics, Central University of Finance and Economics, No. 39, South College Road, Haidian District, Beijing, China, 1000

Journal for Economic Forecasting, 2025, issue 3, 5-23

Abstract: Digital business has entered an unprecedented era with the advent of Generative Artificial Intelligence (GenAI), presenting new opportunities and challenges for high quality development. This study investigates the impact of Artificial Intelligence-Generated Content (AIGC) on firms’ ESG (Environmental, Social, and Governance) performance, drawing on panel data from Chinese listed enterprises between 2003 and 2023, and using a difference-in-differences (DID) method. The result shows that AIGC adoption significantly improves corporate ESG performance, and this finding remains robust across a series of rigorous robustness checks. Further analysis reveals that this effect operates primarily through enhanced corporate digital transformation and green technological innovation. Heterogeneity analysis suggests that the positive effect of AIGC accession is more pronounced among firms located in eastern regions and national computation hubs and among those undergoing digital transformation and being audited by a Big4 accounting firm. These findings offer valuable insights for both firms and policymakers seeking to leverage large models to advance sustainability in the digital economy.

Keywords: AIGC; ESG; ChatGPT (search for similar items in EconPapers)
JEL-codes: D22 O33 Q56 (search for similar items in EconPapers)
Date: 2025
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