Exploring the conditional ESG payoff of AI adoption: The roles of learning capability, digital TMT, and operational slack

Abstract

While many organizations are increasingly willing to adopt artificial intelligence (AI) to support strategic objectives such as sustainable development, the ESG benefits of such adoption are not consistently realized across firms. This study investigates the boundary conditions under which AI adoption contributes to ESG performance. This study aims to investigate when AI adoption contributes to enhanced ESG outcomes by examining key organizational boundary conditions. Specifically, it addresses (1) the association between AI adoption and ESG performance, (2) the moderating roles of learning capability, digital top management team (digital TMT), and operational slack. Using a unique dataset constructed by integrating AI adoption announcements extracted through natural language processing from Factiva and ESG scores obtained from Bloomberg, this study analyzes 8469 firm-year observations from 941 publicly listed manufacturing firms in North America between 2015 and 2022. The results reveal that AI adoption is positively associated with ESG performance. Moreover, this positive effect is amplified by digital TMTs and strong learning capabilities, but weakened by operational slack. These findings enrich the literature on AI-enabled sustainability by highlighting the contingent nature of ESG outcomes and offers managerial insights for firms seeking to align AI strategies with ESG objectives.