While AI is widely recognized as an industrial transformation catalyst, how AI translates into green innovation remains insufficiently understood. Drawing on socio-technical systems theory and upper echelons theory, this study investigates how AI adoption influences green innovation and how managerial cognition shapes this relationship. Using data from Chinese A-share listed firms spanning 2012 to 2024, we reveal that AI significantly promotes green innovation by serving as an endogenous technological force. Managerial cognition (green cognition, innovation cognition, long-termism) serves as a critical boundary condition: all three dimensions positively moderate the AI–green innovation nexus, indicating equivalent technological inputs yield divergent outputs depending on executive interpretation frameworks. Mechanism analyses demonstrate AI operates through three channels: information transparency (improving carbon data quality), compliance internalization (embedding requirements into digital systems), and value creation (transforming environmental data into profit sources). Heterogeneity tests show AI’s effect is more pronounced in high-tech industries and under intense market competition. This study reveals the moderating role of managerial cognition—and its multidimensional construct—in the relationship between AI and green innovation. Practically, it provides actionable insights for cultivating managerial cognition to bridge the gap between AI potential and green innovation realization.
Li et al. (Fri,) studied this question.
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