Pioneers at the AI Frontier: Understanding Early Adopters of Generative AI in Higher Education

Abstract

This study investigates the integration of generative AI in higher education through the theoretical lenses of Rogers' Diffusion of Innovations, Technology Acceptance Model, and Unified Theory of Acceptance and Use of Technology. Through qualitative analysis of twelve semi-structured interviews with business faculty, we examine the interplay between push factors (institutional demands, workload pressures) and pull factors (efficiency gains, innovative pedagogy) shaping AI adoption. The findings reveal four key themes: (1) perceived advantages and efficiency considerations, (2) intellectual engagement and pedagogical alignment, (3) ethical implications and critical judgment, and (4) institutional ambiguity and peer influence networks. While external pressures drive faculty toward AI adoption for teaching and research efficiency, intrinsic motivations spark the exploration of AI's creative affordances. The absence of institutional guidelines leads faculty to rely on informal peer networks for ethical oversight and implementation strategies. The study contributes a novel theoretical framework synthesizing push-pull dynamics with established technology adoption constructs, illuminating the complex interplay between institutional constraints and individual agency in academic AI integration. This research holds implications for developing contextualized ethical guidelines and sustained professional development initiatives to support responsible AI implementation in higher education settings.

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