  We study how humans learn from AI, exploiting an introduction of an
AI-powered Go program (APG) that unexpectedly outperformed the best
professional player. We compare the move quality of professional players to
that of APG's superior solutions around its public release. Our analysis of
749,190 moves demonstrates significant improvements in players' move quality,
accompanied by decreased number and magnitude of errors. The effect is
pronounced in the early stages of the game where uncertainty is highest. In
addition, younger players and those in AI-exposed countries experience greater
improvement, suggesting potential inequality in learning from AI. Further,
while players of all levels learn, less skilled players derive higher marginal
benefits. These findings have implications for managers seeking to adopt and
utilize AI effectively within their organizations.
