Generative AI and ESG opportunism in supply chains : a utilitarian perspective on unintended consequences for sustainability

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Sun, Zhe and Liu, Lei and Zhao, Liang and Alofaysan, Hind and Gupta, Bhumika (2026) Generative AI and ESG opportunism in supply chains : a utilitarian perspective on unintended consequences for sustainability. Technological Forecasting and Social Change, 224. 124498. ISSN 0040-1625 (https://doi.org/10.1016/j.techfore.2025.124498)

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Abstract

Existing research has overwhelmingly emphasized the positive effects of generative artificial intelligence (AI) on corporate environmental, social, and governance (ESG) performance, while largely neglecting the risk of dimensional imbalance in ESG resource allocation and its potential contagion across supply chains. Drawing on utilitarian theory, this study introduces the novel concept of ESG opportunism and empirically examines the impact of generative AI adoption on its emergence and intensity. Results show that generative AI significantly heightens firms’ opportunistic ESG behavior by increasing agency costs and weakening internal controls. This relationship is further amplified by stringent government environmental regulations and strong green investor preferences yet attenuated by greater analyst attention and higher-quality information disclosure. Moreover, a clear supply chain spillover effect is identified: generative AI adoption by focal firms transmits and intensifies ESG opportunism among both upstream suppliers and downstream customers. By challenging the dominant optimistic narrative surrounding generative AI’s ESG implications, this study offers timely and critical insights for establishing responsible generative AI governance throughout global supply chains.

ORCID iDs

Sun, Zhe, Liu, Lei, Zhao, Liang ORCID logoORCID: https://orcid.org/0000-0001-8481-9926, Alofaysan, Hind and Gupta, Bhumika;
CORE (COnnecting REpositories)