Abstract
Background: Generative Artificial Intelligence (GenAI) is transforming higher education by enabling real-time content generation, personalized tutoring, and collaborative learning support. While offering significant learning benefits, AI also raises ethical, pedagogical, and epistemological concerns, particularly across generational cohorts with differing technological literacy, learning styles, and values. Objectives: This study aims to examine intergenerational differences in perceptions of AI as a learning enabler versus a threat to academic rigor and to explore the ethical, pedagogical, and epistemological concerns influencing AI acceptance or resistance, and investigate how these generational attitudes shape classroom practices, power dynamics, and assessment legitimacy. Methodology: A mixed-methods design was employed. Quantitative surveys (~300–400 participants) captured broad generational patterns, while qualitative interviews and focus groups (~10–15 per cohort), classroom observations, and document/discourse analyses explored deeper concerns. Data were analyzed using descriptive and inferential statistics, thematic analysis (Braun & Clarke), and critical discourse analysis with triangulation across sources. Findings/Results: The Gen Z students receive the AI as a personalized learning device. Millennials adopt cautious, hybrid approaches, while Gen X faculty express skepticism, emphasizing academic rigor. Ethical and epistemological tensions were prominent, with students valuing AI outputs pragmatically and faculty questioning their legitimacy. Such diverging perceptions restructure classroom hierarchies, authority and assessment practices and produce tension between institutional policies and student practices. Conclusion: AI adoption in higher education is a restructuring of academic values at a generational level. Universities must adapt policies, pedagogical strategies, and faculty development to integrate AI as a legitimate co-participant in learning, mitigating generational tensions and enhancing engagement, fairness, and educational relevance.