Strategic organisational responses to generative AI-driven digital transformation in leading higher education institutions

Abstract

Purpose This study aims to explore generative artificial intelligence (AI) as a significant milestone and key driver of digital transformation in higher education, emphasising the urgent need for universities and policymakers to adapt strategies to remain effective, competitive and aligned with the rapidly evolving demands of education and research. Design/methodology/approach This study used qualitative content analysis to examine publicly available strategic documents and statements related to digital transformation from the top 30 ranked universities in the Times Higher Education 2024 Ranking, producing a data set of 98 strategies covering all key organisational domains. Findings The collected documents span eight areas, from teaching-learning strategies to information technology (IT) strategies and committees, with substantial variation among universities in scope, content and strategic combinations. A significant result is that teaching-learning offices and development centres serve as bridges between institutional strategies and grassroots innovation, absorbing top-down and bottom-up knowledge andfosteringadaptive responses to generative AI-driven transformation. Practical implications By showcasing the best practices, this paper provides practical guidance for proactive institutional development, supporting university leadership in strategy-building and aiding national and international policymakers in shaping forward-looking frameworks. Originality/value Understanding and defining generative AI as a milestone in digital transformation is crucial for universities. Proactive adaptation to emerging trends and best practices enables institutions to navigate these challenges effectively.