How Customer Artificial Intelligence Technology Drives Supplier Green and Low‐Carbon Efforts: Insights From Green Demand Forcing and Green Knowledge Spillover

ABSTRACT Against the backdrop of increasingly severe climate change threats and the global commitment to achieving net‐zero emissions by 2050, supply chain decarbonization has emerged as a critical climate mitigation strategy. Using data from Chinese A‐share listed companies between 2011 and 2024, this study examines how customer artificial intelligence (AI) technology drives suppliers to adopt green and low‐carbon efforts (GLE). The findings reveal that customer AI technology significantly enhances supplier GLE through two key mechanisms: green demand forcing, where suppliers respond to customers' environmental requirements; and green knowledge spillover, where suppliers absorb and apply customers' green expertise. Further analysis from the supplier‐customer relationship perspective indicates that relational embeddedness, reflected in common ownership, helps align interests and strengthens collaboration between parties, thereby amplifying the positive spillover effects of customer AI technology on supplier GLE. Additionally, these positive effects are more pronounced when structural embeddedness, reflected in high supplier dependence on customers, is present. Heterogeneity tests show that this effect is stronger for suppliers in non‐heavy‐polluting industries and state‐owned suppliers. This study offers a novel theoretical perspective on AI‐driven supply chain decarbonization and provides practical implications for Chinese policymakers striving to achieve net‐zero goals.