Generative AI and the Reinvention of Management Education

Abstract

Generative Artificial Intelligence (GenAI) is rapidly transforming higher education; however, its adoption in management education remains fragmented, with existing studies primarily focusing on conceptual discussions, academic integrity concerns, or isolated classroom applications. Limited research has proposed an integrated framework that combines personalized learning, intelligent tutoring, predictive learning analytics, competency-based assessment, and responsible AI governance within a unified management education ecosystem. To address these gaps, this paper proposes the Generative AI-Enabled Management Education Reinvention Framework (GAI-MERF), an intelligent educational architecture designed to enhance learning outcomes while preserving academic integrity and ethical AI practices. The framework integrates adaptive content generation, AI-driven business case simulations, automated formative assessment, personalized learning recommendations, and predictive analytics to support competency development in strategic thinking, leadership, decision-making, and problem-solving. A quantitative experimental methodology is employed using educational performance data from management students to compare conventional instructional practices with the proposed AI-assisted framework. Multiple evaluation metrics, including academic performance, student engagement, critical thinking, faculty productivity, prediction accuracy, and ethical AI compliance, are used to assess framework effectiveness. Experimental results demonstrate notable improvements across all educational dimensions, indicating that the proposed framework significantly enhances personalized learning, instructional efficiency, and managerial competency development. Furthermore, the integration of transparency, privacy protection, bias mitigation, and human oversight ensures responsible AI adoption within educational environments. The proposed framework provides a scalable and practical foundation for developing intelligent, adaptive, and ethically governed management education systems capable of preparing future business leaders for increasingly AI-driven organizational environments.