Artificial intelligence and corporate green transformation: evidence from China’s A-share listed firms

Purpose This study aims to examine how artificial intelligence (AI) adoption contributes to corporate green transformation. It analyses the mediating roles of green technological innovation and human capital upgrading, the moderating roles of organisational resilience and environmental regulation and the heterogeneous effects across industrial and regional contexts. Design/methodology/approach This study uses panel data on Chinese A-share listed non-financial firms from 2008 to 2023. Fixed-effects regressions, instrumental-variable estimation, propensity score matching, mediation analysis, interaction models and subgroup analyses are used to examine the relationship between AI adoption and corporate green transformation, its transmission mechanisms, boundary conditions and contextual heterogeneity. Findings AI adoption is positively associated with corporate green transformation, and the result remains robust to alternative measures and endogeneity tests. Green technological innovation and human capital upgrading partially mediate this relationship, while organisational resilience and environmental regulation strengthen it. The positive relationship is statistically significant among firms in non-heavily polluting industries, firms in eastern and western China and firms in non-resource-based cities, but not in the corresponding comparison groups. Originality/value This study extends recent evidence on the environmental effects of AI by explaining how AI adoption is converted into firm-level green transformation and why this process varies across firms and locations. It provides an integrated account of the technological, workforce, organisational, institutional and structural conditions that shape the environmental value of AI adoption.