Title: MODELS AND PATHWAYS OF AI-EMPOWERED BUSINESS TALENT CULTIVATION IN CHINA: A GROUNDED THEORY

Authors: Chunjia Hu, Xue Li, Pengbin Gao*

Abstract: The rapid advancement of artificial intelligence is profoundly reshaping the concepts, objectives, and approaches of business talent cultivation. Taking the reform practices of 15 Chinese higher education institutions as research subjects, this study employs grounded theory methodology to code and analyze case literature step by step. This study extracts four core categories—goal adaptation, competency restructuring, pathway reengineering, and ecosystem reshaping—and on this basis constructs a four-stage driven theoretical model of AI-empowered business talent cultivation. The research results indicate that AI-empowered business talent cultivation undergoes a progressive process from “technology embedding” to “model transformation” and then to “ecosystem restructuring”. Institutions first adapt talent cultivation goals based on external environmental changes, then restructure the curriculum system around the composite competency structure of “business + technology”, then realize the transformation of cultivation models through multiple pathways including teaching methods, practical platforms, faculty, and evaluation mechanisms, and finally form a new cultivation ecosystem featuring industry-education integration and collaborative education. The theoretical model proposed in this study reveals the internal logic and evolutionary laws of AI-empowered business talent cultivation, which can provide theoretical references and practical implications for different universities to promote the reform of talent cultivation.

Keywords: Artificial Intelligence, Business Education, Talent Cultivation Model, Grounded Theory.

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