How AI Deployment and External Knowledge Search Shape Innovation Performance

The study presented in this PRICE Seminar adopts the knowledge-based view (KBV) of the firm to explore how deploying artificial intelligence (AI) across organizational functions impacts product innovation performance. The authors propose an inverted U-shaped relationship between AI deployment breadth and innovation performance. They argue that moderate AI deployment promotes cross-functional knowledge recombination by enhancing integration mechanisms. However, excessive AI deployment can lead to knowledge homogenization, reducing innovation returns due to over-reliance on generalizable, codified information and marginalization of context-specific or tacit knowledge. They suggest that deep search in external knowledge sources moderates this relationship, fostering recombination and counteracting homogenization. Analyzing 2,731 Swiss firms (2019–2023), our findings support these hypotheses and contribute to the KBV and innovation literature by emphasizing the need to manage knowledge effectively with AI deployment.