Seeing the spark or the storm? Exploring how AI usage shapes undergraduates’ entrepreneurial intention

Abstract

Drawing on the theory of planned behavior, this study examines how undergraduates' AI usage influences their entrepreneurial intention, exploring both positive and negative pathways. Using data collected from 774 Chinese undergraduates, the study employs ordinary least squares regression and Monte Carlo simulation to test a dual-pathway mediation model, in which opportunity recognition and risk perception mediate the relationship between AI usage and entrepreneurial intention. Additionally, the moderating effects of AI learning and entrepreneurial learning are analyzed within these pathways. The results reveal that AI usage significantly affects entrepreneurial intention indirectly through opportunity recognition and risk perception. Moreover, AI learning strengthens the indirect effect of AI usage via opportunity recognition, while entrepreneurial learning weakens this indirect effect through both opportunity recognition and risk perception. These findings contribute to a more comprehensive understanding of AI usage's influence on entrepreneurial intention and suggest that universities should strategically integrate AI learning with entrepreneurship education to reduce cognitive bias and enhance undergraduates' ability to identify, assess, and validate entrepreneurial opportunities and risks. This study also introduces AI learning and entrepreneurial learning as key boundary conditions, emphasizing the role of educational resources in shaping the dual effects of AI usage on entrepreneurial cognition, and extends the applicability of the theory of planned behavior to the context of emerging technologies, particularly artificial intelligence.