Entrepreneurship Educators’ Acceptance and Use of Generative Artificial Intelligence

Abstract

Despite growing interest in generative artificial intelligence within entrepreneurship education, we lack theory-driven explanations of why or for what purpose entrepreneurship educators adopt these tools in their teaching practice. Addressing this gap, we refined understanding of the Unified Theory of Acceptance and Use of Technology by identifying affinity to technology as an individual-level antecedent and by specifying the boundary conditions under which facilitating conditions lose explanatory power. Using a sequential explanatory mixed-methods design, we first surveyed 380 entrepreneurship educators globally and then conducted 31 interviews to explain the patterns observed in the survey. Our findings show that performance expectancy, effort expectancy, social influence, and affinity to technology significantly shape educators’ intentions to use generative artificial intelligence, which in turn drives actual use. Facilitating conditions, innovativeness, and risk-taking propensity were not significant. Qualitative insights indicate that practical value and ease of use reduce reliance on institutional support, while social influence operates through professional legitimacy rather than proximity-based peers. Overall, we demonstrate that the Unified Theory of Acceptance and Use of Technology helps explain generative artificial intelligence adoption in entrepreneurship education, but only partially, and we clarify the mechanisms through which entrepreneurship educators exercise agency in integrating emerging technologies into their practice.