Artificial intelligence and firms green performance: The mediating roles of product- and customer-oriented servitization strategies

This study examine how artificial intelligence (AI) promotes firms' green performance. Grounded in the resource-based view and service-dominant logic (SDL), we argue that AI technologies improve green performance through two distinct servitization pathways and boundary conditions. Former is by optimizing resource efficiency (product-oriented) and enabling eco-conscious customer solutions (customer-oriented). Latter, contingent on ownership and industry characteristics. Using a longitudinal dataset of 19,150 firm-year observations from Chinese industrial firms (2014–2023), we find robust evidence that artificial intelligence positively impacts green performance through reduced waste and enhanced resource utilization. Empirical analysis reveals that customer-oriented servitization mediates the AI–green performance relationship more strongly than product-oriented servitization, though both are significant partial mediators. Further, the effects are heterogeneous: AI's impact is most pronounced in state-owned enterprises and heavy industries, where institutional resources and scale amplify servitization's green benefits. This research contributes to the literature on AI and green performance by theorizing and empirically validating product- and customer-oriented servitization strategies as a critical mediating mechanism. It differentiates the green efficacy of product- versus customer-oriented strategies, and identify ownership nature and industry contexts that shape AI's green outcomes. For practitioners, our findings emphasize the importance of aligning AI investments with servitization strategies tailored to firm-specific contexts to maximize sustainability gains.