Integrating artificial intelligence in entrepreneurship education: Dynamic capabilities and marketing performance among student entrepreneurs

Abstract

The rapid integration of artificial intelligence (AI) technologies in business education presents both opportunities and challenges for developing entrepreneurial competencies among students. This study examines how AI adoption influences marketing performance through dynamic capabilities and organizational flexibility in the context of student entrepreneurship education. Drawing on a longitudinal survey of 434 student entrepreneurs across universities in Eastern China, we employ a dual-stage analytical framework combining PLS-SEM and fsQCA to investigate the multifaceted relationships between AI drivers, dynamic capabilities, and marketing outcomes. Our findings reveal that technology-driven, organization-driven, environment-driven, and human-driven factors of AI positively influence students' dynamic capabilities—sensing, seizing, and reconfiguring—which subsequently enhance their AI-enabled marketing performance. Organizational flexibility emerges as a significant positive moderator in this relationship. The fsQCA analysis identifies six configurations leading to optimal marketing performance, providing nuanced insights for curriculum design. These findings contribute to management education literature by demonstrating how AI integration can enhance entrepreneurial learning outcomes and inform pedagogical approaches. The study offers practical implications for educators seeking to prepare students for AI-driven business environments while advancing responsible management education aligned with sustainable development goals.