The learning paradox: why educators must unlearn to embrace generative AI

Purpose – Generative AI is changing every facet of life, including higher education. Educators are not immune to this disruption, which challenges their traditional mindsets. This paradigm shift requires critical reflection for educators to unlearn and relearn generative AI’s possibilities. This study explores how higher education educators must approach unlearning traditional teaching practices to adopt generative AI effectively. Design/methodology/approach – The study applies a conceptual approach to explore using organizational unlearning theory as a pathway for meaningful generative AI integration. The conceptual integration of organizational unlearning and digital maturity is adopted to map multiple stages for higher education educators to integrate GenAI as an assistant. Findings – Five nonlinear maturity stages are proposed for higher education educators to adopt practically: (i) foundation awareness, (ii) educational experimentation, (iii) strategic implementation, (iv) transformational practice, and (v) educational ecosystem architects. Each stage reflects on recognition activities, unlearning levels, and key actions to realize generative AI’s integration. Research limitations/implications – The conceptual approach requires empirical exploration to formalize the maturity framework in higher education. Practical implications – The maturity stages provide a framework for progressive integration by starting with low-stakes GenAI experiments. The five stages require extensive introspection of how generative AI influences operational and transformational stages to architect an innovative higher education environment. Originality/value – Organizational unlearning is an underexplored concept in higher education. This study provides a conceptual framework for initiating higher education unlearning in the generative AI era.