The rapid advancement of artificial intelligence (AI) is fundamentally transforming the global workforce, challenging the relevance and effectiveness of traditional higher education models. This paper argues that the long-standing academic major, rooted in rigid disciplinary boundaries and slow to adapt, is increasingly misaligned with the demands of a dynamic, AI-driven world. In response, we propose a shift toward modular, AI-centric learning paths as a more flexible, personalized, and future-ready alternative. Through a critical examination of the limitations of the current system - including inflexibility, siloed knowledge, skill mismatches, and lack of lifelong learning support - we highlight the urgent need for educational reform. We then present a compelling case for modular learning, emphasizing its ability to foster interdisciplinary thinking, embed AI literacy across all fields, and support the development of transferable, in - demand skills. This model empowers students to build customized, stackable credentials aligned with evolving career opportunities. The paper concludes with a comprehensive set of recommendations for implementing this transformation, including faculty development, industry collaboration, updated accreditation standards, and the integration of AI - powered learning technologies. By embracing modular, AI-integrated education, institutions can better prepare graduates for the complexities of the 21st-century workforce and ensure higher education remains relevant, inclusive, and responsive in the age of AI.
Jingyo Suh (Mon,) studied this question.
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