Sensing, Seizing, and Transforming: How AI Adoption Enhances Green Dynamic Capabilities in High-Tech Enterprises

The integration of artificial intelligence (AI) into corporate sustainability strategies has gained significant attention, yet the mechanisms through which AI adoption enhances green innovation remain underexplored. Drawing on dynamic capabilities theory, this conceptual paper examines how AI adoption enhances green dynamic capabilities, specifically sensing, seizing, and transforming capabilities, to drive green innovation in high-tech enterprises. Through a systematic review and synthesis of 24 empirical studies published between 2021 and 2026, an integrated conceptual framework is developed proposing that AI adoption does not directly lead to green innovation but rather operates through the mediating mechanism of green dynamic capabilities. Organizational readiness and environmental dynamism are further identified as key moderators that influence the effectiveness of this mediated relationship. The paper advances a set of nine testable propositions and presents a comprehensive model that distinguishes how each dimension of green dynamic capabilities (sensing, seizing, transforming) is differentially enhanced by specific AI applications. Theoretical contributions include extending dynamic capabilities theory to the AI green innovation context, clarifying the mediating role of green dynamic capabilities, and integrating contingency factors that shape AI-enabled green innovation. Practical implications for managers and policymakers in high-tech sectors are discussed. The paper acknowledges its conceptual nature and reliance on existing literature as key limitations, and a research agenda for future empirical validation across diverse organizational settings is proposed.

Artificial intelligence adoption, green dynamic capabilities, green innovation, high-tech enterprises, dynamic capabilities theory

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