Adoption of Artificial Intelligence Tools and Sustainable Management of Educational Facilities in Public Universities, Kwara State, Nigeria

Educational facilities in Nigerian public universities face increasing infrastructural strain due to rising student populations and outdated maintenance practices, necessitating innovative solutions such as Artificial Intelligence (AI) for sustainable management. This study investigated the adoption of AI tools and the sustainable management of educational facilities in public universities within Kwara State, Nigeria. To provide a robust analytical foundation, the study was anchored on the Technology-Organisation-Environment (TOE) framework and the Technology Acceptance Model (TAM), as these theories collectively explain how institutional infrastructure, organizational structures, and user perceptions shape the adoption of technological innovations such as AI tools in facility management. A descriptive survey research design was employed, targeting administrative staff, estate managers, and physical planning personnel across selected public universities (N=346). A stratified random sampling technique produced a sample size of 185 respondents. Data were collected using a validated instrument titled Artificial Intelligence Tools and Sustainable Facilities Management Questionnaire (AITSFMQ), with a pilot reliability coefficient of 0.86. Descriptive statistics (frequency, percentage, and mean) were used to answer research questions, while Pearson product moment correlation (PPMC) tested hypotheses at a 0.05 significance level. Findings revealed that adoption levels of AI tools, particularly predictive maintenance algorithms and IoT-enabled energy tracking systems remain low. Nonetheless, a significant positive relationship was established between AI integration and sustainable facility management outcomes (r = 0.618, p < 0.05). Key barriers include inadequate technological infrastructure, high initial capital requirements, and low digital literacy among facility managers. The study recommends institutionalizing public-private partnerships to subsidize AI-driven infrastructural upgrades and organizing targeted capacity-building workshops to enhance digital competence among facility management staff.

Artificial Intelligence, Sustainable Management, Educational Facilities, Public Universities, Kwara State.

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