How Do AI Capabilities Affect Ambidextrous Green Innovation? A Mechanistic Analysis Based on Green Knowledge Management and Human–Organization–Technology Fit

Although artificial intelligence (AI) capabilities have emerged as a critical driver of corporate innovation in the contemporary business landscape, how they facilitate ambidextrous green innovation (AGI) during the manufacturing sector’s green transition—and under what conditions these benefits are most pronounced—remains unclear. Drawing on the Resource-Based View (RBV) and Knowledge-Based View (KBV), this study investigates the mechanism by which AICs foster AGI through the mediating role of green knowledge management (GKM), while further examining how Human–Organization–Technology (HOT) fit moderates these pathways. An analysis of survey data from 238 Chinese manufacturing firms using PLS-SEM reveals that AICs significantly drive AGI, with GKM playing a pivotal mediating role. Furthermore, the study confirms that Human–Organization–Technology (HOT) fit acts as a boundary condition, moderating the impact of AICs on GKM. These findings clarify the underlying mechanisms and boundary conditions of AICs, offering actionable insights for manufacturers seeking to boost green innovation capabilities by optimizing HOT alignment and leveraging green knowledge management systems.