Exploring Generational Perspectives on AI Use in Higher Education: A Theory - Jesus, Jiomarie; Basilisco, Genessa; Gemodo, Khay-c G.; E. Espiloy, Gloria; M. Lucero, Cheryl; M. Sumilhig, Jeffy (ASEAN Journal of Management & Innovation, 2025)
Higher education is changing as a result of artificial intelligence (AI), nevertheless, different generations are still adopting AI at different levels because of differences in trust, digital literacy, and ethical concerns. The use, perceptions, and integration of AI in academic settings are examined in this study concerning generational identity. 10 key informants from Metro Cebu were carefully selected and interviewed using a qualitative grounded theory methodology. Millennial instructors and postgraduate students, Gen X and Baby Boomer administrators, Gen Z students, and institutional technology facilitators were among them. To uncover significant patterns, semi-structured interviews were analyzed using open, axial, and selective coding, strengthened by in progress comparative analysis. Four main themes emerged: cross-generational innovation, peer influence and digital practices, institutional support and ethical considerations, and generational attitudes toward AI. These influenced the creation of the Generationally Mediated AI Adoption Theory (GMAIAT), an innovative framework that suggests that complex generational mediation across cognitive, cultural, and normative dimensions determines AI adoption in higher education instead of simply technological access or perceived usefulness. Through the integration of generational perspectives with UTAUT and TPB constructs, this work contributes to the growing discussion on AI in education. It provides practical suggestions for creating frameworks for ethical AI use, inclusive digital education policies, and cross-generational professional growth. The results highlight the value of institutional preparedness and intergenerational communication in promoting ethical and long-term AI integration in higher education.