Reimagining entrepreneurship education in the ai era within resource- constrained settings: a pedagogical renaissance

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How can artificial intelligence (AI) technologies transform entrepreneurship education (EE) in resource-constrained settings?This study explores this question through an investigation of technology adoption at a South African university.Our findings reveal three key phenomena that challenge conventional views on digital transformation in higher education.First, students often lead technological innovation informing faculty in using AI agents and platforms.Second, resource limitations drive what we term "adaptive digital bricolage," where basic AI technologies are combined in creative ways to achieve advanced EE outcomes.Third, rather than eroding traditional practices, AI platforms can preserve and enhance indigenous entrepreneurial knowledge.Using an integrated theoretical framework by drawing from the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT) and Technological Pedagogical Content Knowledge (TPACK), we show that successful digital transformation depends more on leveraging local innovation than on significant resource investment.These findings offer new insights for institutions operating in resourceconstrained environments, suggesting pathways to achieve technological advancement while preserving local knowledge systems.

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