Manufacturing Enterprises' AI Capabilities Drive Product Innovation: A Moderated Mediating Model of Organizational Sensing-Responsiveness Capability and Digital Leadership An Empirical Study of Advanced Manufacturing Small and Medium Enterprises in the Yangtze River Delta and the Pearl River Delta

Abstract

Against the backdrop of deep fusion between the digital economy and the real economy artificial intelligence has surfaced as a pivotal engine through which manufacturing firms surmount growth ceilings and pursue high quality development. But much existing research still assumes that AI investment automatically leads to innovation output and it ignores the deeper pathways and leadership boundary conditions of the transformation. Based on the resource based view and dynamic capabilities theory, this study proposes a moderated mediation model to intertwine enterprise artificial intelligence capabilities (both technology and talent, and process), organizational sensing responsiveness capability, and digital leadership. 160 advanced technology small and medium manufacturing enterprises were surveyed using a multiple source paired questionnaire, which was completed on an online survey form, from the Yangtze River Delta cluster of Suzhou and the Pearl River Delta cluster of Dongguan. Partial least squares structural equation modeling and subgroup regression gave rise to three key conclusions. AI capability has multiple dimensions that drive innovation in fundamentally different ways: Technological infrastructure and human capital have a strong linear drive, while AI-driven process culture has an inverted concave function, confirming that over-standardization leads to core rigidity. Organizational sensing responsiveness capability is a partially mediating conduit between technological potential and market momentum. Digital leadership is a double-edged moderating force that turns on infrastructure and boosts agility while stifling talent autonomy.