Artificial Intelligence Adoption and Implementation in Zambia’s Public UniversityLibraries: Behavioural Intention, Technologies and Institutional Factors

Matuka Chipembele; William Abwino Phiri; Euphrasia Ngandwe

Artificial Intelligence Adoption and Implementation in Zambia’s Public UniversityLibraries: Behavioural Intention, Technologies and Institutional Factors

Author(s)	Mr. Matuka Chipembele, Prof. William Abwino Phiri, Dr. Euphrasia Ngandwe
Country	Zambia
Abstract	This study examined artificial intelligence (AI) adoption and implementation in the public university libraries of the University of Zambia, Copperbelt University, Chalimbana University and Mukuba University. Guided by the Technology–Organisation–Environment framework, UTAUT2, Diffusion of Innovations and Institutional Theory, it adopted a pragmatist paradigm and convergent parallel mixed-methods design. Quantitative data were collected from students, complemented by interviews with 13 key informants and documentary analysis. Quantitative data were analysed using descriptive statistics, Pearson product-moment correlation, and multivariate regression analysis in SPSS Version 31, while qualitative data were analysed thematically. A sample of 398 respondents was determined using Yamane’s formula, and 398 questionnaires were distributed, of which 343 were completed and returned, representing an 86.2% response rate. Of 343 respondents, 309 (90.1%) were aware of AI-enabled tools, while 277 (89.6%) of those aware recognised AI assistants and writing coaches. Daily or weekly use was reported by 253 respondents (82.1%). However, access was predominantly independent, and reviewed strategic plans contained no explicit AI provisions. Performance expectancy, compatibility and effort expectancy significantly predicted behavioural intention, with the technological model explaining 45.5% of its variance. Facilitating conditions and AI literacy were also significant predictors, explaining 22.1%. Behavioural intention significantly predicted AI implementation, accounting for 32.7% of its variance. Qualitative findings highlighted leadership support, funding, infrastructure, governance, ethics, staff training and organisational culture as important contextual conditions. The study identifies a gap between widespread individual AI engagement and limited formal institutional integration, highlighting the need for strategic alignment, stronger infrastructure, AI literacy and clear governance.
Keywords	Artificial Intelligence, Academic Libraries, Behavioural Intention
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 17, Issue 4, October-December 2026
Published On	2026-10-26

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Artificial Intelligence Adoption and Implementation in Zambia’s Public UniversityLibraries: Behavioural Intention, Technologies and Institutional Factors

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