Artificial intelligence and the changing sources of competitive advantage - Krakowski, Sebastian; Luger, Johannes; Raisch, Sebastian (Strategic Management Journal, 2023)
Abstract Research Summary We apply a resource‐based view to investigate how the adoption of Artificial Intelligence (AI) affects competitive capabilities and performance. Following prior work on using chess as a controlled setting for studying competitive interactions, we compare the same players’ capabilities and performance across conventional, centaur, and engine chess tournaments. Our analysis shows that AI adoption triggers interrelated substitution and complementation dynamics, which make humans’ traditional competitive capabilities obsolete, while creating new sources of persistent heterogeneity when humans interact with chess engines. These novel human‐machine capabilities are unrelated, or even negatively related, to traditional capabilities. We contribute an integrated view of substitution and complementation, which identifies AI as the driver of these dynamics and explains how they jointly shift the sources of competitive advantage. Managerial Summary AI‐based technologies increasingly substitute and complement humans in managerial tasks such as decision making. We investigate how such change affects the sources of competitive advantage. AI‐based engines’ adoption in chess allows us to investigate competitive capabilities and performance in human, AI, and hybrid settings. We find that neither humans nor AI in isolation explain performance differences in the AI and hybrid settings. Instead, a new decision‐making resource emerges at the human‐AI intersection, which drives performance but is unrelated or even negatively related to humans’ original capability. Our results document how AI adoption changes the sources of competitive advantage and, in turn, requires managers to develop new capabilities to stay relevant in an AI‐based competitive landscape.