Is More Transparency Always Better? The Dilemma of AI-enabled ESG Disclosure in Supply Chains with Information Distortion

This paper investigates how AI-enabled ESG management reshapes operational decisions in a supplier–retailer supply chain characterized by responsibility investment, information distortion, and consumer privacy concerns. We develop a game-theoretic model in which the supplier determines responsible input with a certain disclosure strategy, while the retailer decides whether to adopt AI for ESG reporting. The analysis shows that the supplier’s greenwashing or brownwashing behavior critically moderates the impact of AI adoption: when disclosure distortion is mild, AI enhances transparency, stimulates demand, and increases responsible input, whereas strong greenwashing weakens or even reverses these effects. The retailer’s AI adoption incentive depends on the interaction between disclosure distortion and penalty allocation, generating distinct adoption regions under different regulatory exposures. From the stakeholder perspective, consumer privacy sensitivity and information distortion jointly affect the impacts of AI on consumer surplus and social welfare. Overall, the results highlight the contingent value of AI-enabled ESG and offer managerial guidance on technology adoption, penalty design, and data-governance strategies in sustainable supply chain management.