AUTHOR=Guan Dian , Wang Zexia , Han Wucheng , Pei Yinqiang 
  
TITLE=Artificial intelligence usage, breakthrough innovation, and innovation performance in high-tech enterprises: the nonlinear moderating role of Not-Invented-Here Syndrome
  
JOURNAL=Frontiers in Artificial Intelligence
  
VOLUME=Volume 8 - 2025
  
YEAR=2026
  
URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1699860
  
DOI=10.3389/frai.2025.1699860
  
ISSN=2624-8212
  
ABSTRACT=The integration of artificial intelligence (AI) with frontier technologies such as large language models and quantum computing has significantly enhanced enterprises’ potential for breakthrough innovation, becoming a critical driver of innovation performance. However, the internal mechanisms and boundary conditions through which AI influences innovation performance via breakthrough innovation remain unclear, requiring further exploration to deepen our understanding of AI’s crucial role in organizational innovation. Drawing on the resource-based view (RBV), this study systematically investigates the impact of AI use on innovation performance, emphasizing the mediating role of breakthrough innovation and the moderating effect of Not-Invented-Here Syndrome (NIHS). Data were collected from 355 global high-tech enterprises via the Prolific platform and analyzed using partial least squares structural equation modeling (PLS-SEM). The findings demonstrate that AI use positively impacts innovation performance, with breakthrough innovation serving as a significant mediator. NIHS exhibits an inverted U-shaped moderating effect on the relationship between AI use and innovation performance, while displaying a U-shaped moderating effect between breakthrough innovation and innovation performance. This study provides initial empirical evidence that AI promotes breakthrough innovation in high-tech enterprises, thus enhancing innovation performance, unveiling the ‘black box’ of how AI influences innovation performance through breakthrough innovation. Moreover, it explores the nonlinear moderating role of NIHS, reinforcing the applicability of RBV in the digital era. This research also offers practical guidance for high-tech enterprises to optimize resource allocation and implement breakthrough innovation strategies in AI-driven innovation environments to achieve superior innovation performance and competitive advantage.