Please use this identifier to cite or link to this item: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/30494
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dc.contributor.authorBakare, M.A-
dc.contributor.authorGambari, A. I.-
dc.contributor.authorAgboola, K.A-
dc.contributor.authorSobowale, F. M.-
dc.contributor.authorFolohunsho, T.-
dc.date.accessioned2026-04-02T21:57:46Z-
dc.date.available2026-04-02T21:57:46Z-
dc.date.issued2025-
dc.identifier.citationBakare M.A, Gambari, A. I., Agboola K.A, Sobowale, F. M., Folohunsho, T. (2025) INSIGHT INTO THE MULTI-PREDICTIVE FACTORS INFLUENCING ARTIFICIAL INTELLIGENCE (AI) ADOPTION IN UNIVERSITY ADMINISTRATION IN NORTH-CENTRAL NIGERIA. 11th International Conference of School of Science and Technology Education (SSTE)en_US
dc.identifier.urihttp://irepo.futminna.edu.ng:8080/jspui/handle/123456789/30494-
dc.description.abstractThe use of artificial intelligence (AI) is fast taking over the academic terrain as well as other professions. It is also used in university system administration, though to a limited scope. This study sheds light on the various factors that influence the adoption of AI in university administrative systems in North-Central Nigeria. Using the Technology–Organization–Environment (TOE) framework and the Diffusion of Innovation (DOI) theory as a guide, the research explores key elements such as technological infrastructure, staff training and digital skills, perceived usefulness, organizational readiness, leadership support, and resistance to change. The paper examines the multi-dynamics of AI adoption in the university administrative system, specifically in North-central Nigeria. The categories of multi-predictive factors: technological and organizational readiness, influence of external environment and social attitudes towards adoption of AI are examined. The challenges of adopting AI in the university system, the panacea to the identified problems and the ethical implications are discussed. This study adds to the existing knowledge by emphasizing the complex interplay of technological, organizational, and human factors that shape AI adoption in higher education administration. The practical implications suggest that policymakers and university leaders should focus on enhancing digital infrastructure, building capacity, and implementing effective change management strategies to promote a sustainable AI-driven transformation.en_US
dc.publisher11th International Conference of School of Science and Technology Education (SSTE), FUT Minna, Nigeriaen_US
dc.subjectArtificial Intelligence, University Administration, Adoption, Multi-predictive Factors, North-Central Nigeria, TOE framework, DOI theoryen_US
dc.titleINSIGHT INTO THE MULTI-PREDICTIVE FACTORS INFLUENCING ARTIFICIAL INTELLIGENCE (AI) ADOPTION IN UNIVERSITY ADMINISTRATION IN NORTH-CENTRAL NIGERIAen_US
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