Artificial Intelligence Applications and Corporate Sustainable Development: An Economic and Environmental Performance Perspective

Huixin Sun; Rongchun Zhu

doi:10.31181/ijes1512026234

Authors

Huixin Sun School of Economics and Management, Xinjiang University, Urumqi, Xinjiang, China Author https://orcid.org/0009-0006-6465-7986
Rongchun Zhu School of Economics, Xinjiang University of Finance and Economics, Urumqi, Xinjiang, China Author https://orcid.org/0009-0007-4964-659X

DOI:

https://doi.org/10.31181/ijes1512026234

Keywords:

Artificial Intelligence, Corporate Sustainable Development Performance, Financial Performance, Environmental Performance

Abstract

Against the backdrop of rapid advancements in intelligent technologies and the convergence of China's "dual carbon" strategic goals, how enterprises leverage artificial intelligence to enhance economic and environmental benefits while achieving sustainable development has emerged as a critical research question. This study adopts a dual-perspective approach, examining both financial and environmental performance within the framework of sustainable development. Based on a sample of Chinese A-share listed companies from 2013 to 2023, this study employs a multi-period Difference-in-Differences model to empirically examine the impact of applications of artificial intelligence on corporate sustainable development performance, as well as the underlying mechanisms. The findings reveal: (1) Applications of artificial intelligence enhance both the financial and environmental performance of corporations, thereby improving their overall sustainable development performance. The conclusion has passed a series of robustness tests, including heterogeneity tests and double machine learning. (2) Mechanism analysis reveals that artificial intelligence influences corporate sustainable development performance through green innovation effects, efficiency enhancement effects, and information acquisition effects. The Porter Hypothesis, the Resource-Based View, and the Information Asymmetry Theory, among other theories, have been verified. (3) The promotional effect of artificial intelligence applications on sustainable development performance exhibits heterogeneity. Specifically, the promotional effect is more pronounced in non-heavily polluting enterprises, high-tech enterprises, and enterprises with senior executives possessing environmental protection backgrounds. (4) When enterprises are engaged in intense market competition, the positive relationship between artificial intelligence adoption and sustainability performance strengthens. Our findings offer valuable insights for managers and policymakers aiming to leverage AI for achieving sustainable growth.

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