Gaessler, FabianPiezunka, Henning2023-07-122023-07-122023Gaessler F, Piezunka H. Training with AI: evidence from chess computers. Strateg Manag J. 2023;44(11):2724-50. DOI: 10.1002/smj.35120143-2095http://hdl.handle.net/10230/57555We suggest that AI can help decision-makers learn; specifically, that it can help them learn strategic interactions by serving as artificial training partners and thus help them to overcome a bottleneck of scarce human training partners. We present evidence from chess computers, the first widespread incarnation of AI. Leveraging the staggered diffusion of chess computers, we find that they did indeed help chess players improve by serving as a substitute for scarce human training partners. We also illustrate that chess computers were not a perfect substitute, as players training with them were not exposed to and thus did not learn to exploit idiosyncratic (“human”) mistakes. We discuss implications for research on learning, on AI in management and strategy, and on competitive advantage.application/pdfeng© 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1002/smj.3512artificial intelligencechessdifference-in-differenceslearningstrategic interactioninfo:eu-repo/semantics/openAccess