Knowledge enablers and barriers in generative AI adoption: educator perspectives from higher education

Abstract

Purpose Generative artificial intelligence (GenAI) is transforming management practices, enabling the free flow of knowledge and enhancing learning ecosystems from which education branches. While it brings many opportunities, it also causes some problems. Those problems are serious but small in scale. This study aims to examine how management educators perceive, use and adapt GenAI tools for their instructional and evaluative activities. Design/methodology/approach To gather data, the researchers did 40 interviews with faculty members from different universities. The researchers used a range of theories in their study. Specifically, they used Gioia’s approach along with the knowledge management theory, unified theory of acceptance and use of technology 2, the diffusion of innovations social cognitive theory, as well as the theory of activities. Findings Results paint a storyline. Some educators view GenAI as a game-changer and are finding ways to enhance student interaction while reducing the time spent creating learning materials. They highlight issues such as policies, ethics, over-reliance and threats to academic integrity. In essence, teachers are far from passive adopters. They also negotiate on mechanisms and approaches that are context-sensitive, assessing costs, benefits and the risks involved. Practical implications To support the responsible use of GenAI, regulatory frameworks, adequate training protocols and effective monitoring systems are necessary. This research shows how a teacher’s voice can help higher education institutions to use AI to better effect without losing their standards and values. Originality/value The research incorporates ideas from multiple frameworks that help clarify the enablers and constraints of GenAI adoption. This helps both researchers and practitioners in the field.

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