Harnessing artificial intelligence for ambidextrous innovation: Contingent roles of complementary investments

While a growing body of literature has explored the role of artificial intelligence (AI) in innovation management, current research lacks understanding of how AI adoption affects firms' ambidextrous innovation and what contextual factors may influence this relationship. Drawing on the innovation search perspective and upper echelons theory, this study theorizes the impact of AI adoption on ambidextrous innovation and evaluates the contingent roles of complementary investments. Using panel data from Chinese listed firms between 2011 and 2022, we find strong evidence that AI adoption significantly increases exploratory innovation (ERI) and exploitative innovation (EII). The mechanisms by which AI adoption affect ERI and EII involve broadening and heightening the scope and depth of knowledge search, respectively. Moderating analyses reveal that executives’ features (e.g., educational level and tenure) exert varying contingent effects. Specifically, executive educational level amplifies the positive impact of AI on EII but has no significant role in the AI–ERI relationship. Furthermore, executives with longer tenure tend to diminish the positive effect of AI on ERI and EII. These findings contribute to the existing literature at the intersection of AI and innovation and provide insights into how firms should make complementary investments to fully capture the benefits of AI.