Greenwashing Governance through ESG Disclosure: A Double Face for Artificial Intelligence - Zhang, Hanwen (Exploring Science Academic Conference Series, 2026)
The growing use of artificial intelligence (AI) in producing, interpreting, and verifying information on the environmental, social, and governance (ESG) information. Companies are under increasing pressure to report on ESG information that is extensive, useful, credible, comparable, and decision-useful. However, the proliferation of ESG disclosure does not guarantee more transparency. Rather, it has increased the risk of symbolic disclosure, narrative inflation, and greenwashing. In this context, AI is emerging as an attractive governance technology but also as a new source for reporting risk. In this narrative review, we discuss how AI could influence ESG disclosure quality, or even the governance of greenwashing. Here, we argue that we need to understand AI beyond its use as a technological solution to process sustainability information, but also as a socio-technical form of governance that transforms the production, evaluation, and contestation of sustainability claims. Drawing from the literature on ESG disclosure, greenwashing, computational text analysis, sustainability reporting and ESG assurance, our contribution is to develop a three-level framework in which AI can be used both as a disclosure mechanism and as an audit instrument, with the potential of also promoting indirect normative behavior. The work presented here builds on this triple role of AI. We find AI can improve ESG disclosure through automated processing and anti-greenwashing monitoring, yet generative AI may enable sophisticated symbolic compliance. AI offers opportunities for ESG disclosure and governance, but its actual effects depend on organizational incentives, disclosure environments, and accountability mechanisms.