Title Pending 1076
Year: 2025
Type: article
Study design: Observational Study
Abstract: This is an accepted article with a DOI pre-assigned that is not yet published.This study investigates artificial intelligence (AI) literacy and adoption readiness among 102 librarians in private university libraries in Osun State, Nigeria, using the Technology Acceptance Model (TAM). A quantitative survey across eight institutions reveals high AI awareness (87.3%, mean = 3.18 on a 4-point Likert scale) and positive perceptions (57.8% strongly agree AI is transformative, mean = 3.42), surpassing Nigeria’s public university benchmarks (65%). Chi-square tests (p > 0.05) and regression (R² = 0.058, p = 0.119) show no significant variation by qualifications, position, or experience, while ANOVA (F = 3.497, p = 0.001) identifies institutional differences (e.g., Adeleke mean = 3.40 vs. Bowen mean = 2.95). Sensitivity analysis (standardized difference = 0.23) highlights Likert scales’ superiority over binary measures in detecting variance. Extending TAM, the study positions awareness as a stable antecedent to perceived usefulness, moderated by institutional factors rather than demographics—a novel refinement in library and information science (LIS). Despite high awareness, practical AI use remains limited, reflecting infrastructural and training gaps. Findings contrast with public-sector studies and align with global trends (80% awareness in developed contexts), offering a developing-region lens on AI readiness. Recommendations include institution-specific training (₦500,000/library) and pilot investments (₦2 million/library) to bridge adoption gaps. This research advances TAM’s application in LIS, contributes to AI literacy discourse, and informs strategic planning for technology integration in resource-constrained academic libraries, with implications for global-south contexts.
DOI: 10.7191/jeslib.1076
Authors: Adekunle Victor Alao, Afolabi Olajide
Institutions: Bowen University, Precious Cornerstone University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4412499495