Artificial Intelligence Adoption in Higher Education Administration: Leadership, Governance and Organisational Implications
DOI:
https://doi.org/10.15680/IJCTECE.2025.0805038Keywords:
Artificial Intelligence, Higher Education, Digital Leadership, AI Governance, Organisational Readiness, Administrative TransformationAbstract
As the operations of higher education institutions grow more complex, artificial intelligence (AI) is increasingly being recognized as a vital tool in the administration of education.Institutions are looking for ways to manage with greater speed, responsiveness, data-informed, and efficient operations and ways to leverage artificial intelligence (AI) as a tool in higher education administration. In this article, we explore the phenomenon of AI adoption through the lens of leadership readiness, governance frameworks and organisational implications. Special focus is placed on executives' readiness, institutional responsibility, administrative reorganisation, staff adaptation, operational effectiveness, ethical dangers, data security and institutional capacities. This study takes the comparative case-study approach with a qualitative analysis of institutional practices and documented AI applications. It examines the impact of decision making by leaders, governance structures and organizational environments on the effectiveness and sustainability of administrative systems enabled by AI. The expected results indicate that if technology is to be adopted and used successfully, it is necessary to have a clear policy of oversight, competent staff and policy and institutional readiness to support the technology. The article stresses the importance of a combination of innovation and a human approach that includes ethical protection measures and ongoing organizational learning
References
[1] Chen, L., P. Chen, and Z. Lin. “Artificial Intelligence in Education: A Review.” IEEE Access, vol. 8, 2020, pp. 75264–75278. doi:10.1109/ACCESS.2020.2988510.
[2] Cyber, in, et al. “Data Privacy-Aware Machine Learning and Federated Learning: A Framework for Data Security.” American Journal of Interdisciplinary Studies, vol. 02, no. 03, 1 Sept. 2021, pp. 01–34. doi:10.63125/vj1hem03.
[3] de Almeida, Patricia Gomes Rêgo, et al. “Artificial Intelligence Regulation: A Framework for Governance.” Ethics and Information Technology, vol. 23, no. 3, 21 Apr. 2021, pp. 505–525. doi:10.1007/s10676-021-09593-z.
[4] Keding, Christoph. “Understanding the Interplay of Artificial Intelligence and Strategic Management: Four Decades of Research in Review.” Management Review Quarterly, vol. 71, no. 1, 24 Feb. 2020. doi:10.1007/s11301-020-00181-x.
[5] Kurup, Sreejith, and Vivek Gupta. “Factors Influencing the AI Adoption in Organizations.” Metamorphosis: A Journal of Management Research, vol. 21, no. 2, 18 Sept. 2022, pp. 129–139. doi:10.1177/09726225221124035.
[6] Nortje, M. A., and S. S. Grobbelaar. “A Framework for the Implementation of Artificial Intelligence in Business Enterprises: A Readiness Model.” 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Cardiff, UK, 2020, pp. 1–10. doi:10.1109/ICE/ITMC49519.2020.9198436.
[7] Pedró, Francesc. “Applications of Artificial Intelligence to Higher Education: Possibilities, Evidence, and Challenges.” IUL Research, vol. 1, no. 1, 24 July 2020, pp. 61–76. doi:10.57568/iulres.v1i1.43.
