Go beyond the Local Search: Understanding the Impact of AI Capabilities on Exploratory Innovation

Myunghwan Lee, Gene Moo Lee, Cui, Victor. “Go beyond the Local Search: Understanding the Impact of AI Capabilities on Exploratory Innovation”, AOM 2023

Firms typically depend on technological assets or inter-firm relationships to pursue exploratory innovation. In this paper, we regard Artificial Intelligence (AI) as an exploratory innovation-seeking instrument by which AI may search unexplored resources and thereby broaden the boundary of a firm. Drawing on the theory of bounded rationality and organizational learning, we hypothesize the impact of a firm’s AI capabilities on exploratory innovation and how AI influences traditional boundary-expanding activities. Our empirical investigations, using a novel AI capabilities measure constructed with AI conference and patent datasets, show that AI capabilities have positive impacts on exploratory innovation. In addition, the results show that extant technological assets (i.e., traditional data management capabilities) and ongoing inter-firm relationships (i.e., inter-firm technology collaboration) remedy the constraints on a firm’s innovation-seeking behaviors and that these boundary-expanding activities negatively moderate the positive impact of AI capabilities on exploratory innovation. Our key takeaway is that we investigate how AI affects exploratory innovation using our newly developed AI capability measure, contributing to the body of knowledge on exploratory innovation literature.