Meeting the AI demand: Challenges and prospects for content diversification in southwestern Nigerian universities academic library consortia

Abstract

The growth in demand for the implementation of artificial intelligence (AI) applications in academic library consortia has raised the demand for strategic diversification of content to meet evolving users' expectations. This study discussed the challenges and opportunities of integrating AI into content management and provision of services in academic library consortia. Based on the Innovation Diffusion Theory and the Resource-Based View, the researcher utilised qualitative dominant mixed methods with systematic literature review, semi-structured interviews from consortium administrators, ICT heads, and senior librarians in selected libraries, and document analysis of strategic plans and policy frameworks. The population of the study is 75 consortium administrators and sample size across five selected universities in Southwestern Nigeria is 30 purposively selected participants. Thematic analysis was employed to code and interpret qualitative data in a systematic way, and to reveal main patterns and themes on AI demand and content diversification. Findings indicate that while AI offers unprecedented opportunities for resource discovery, personalized services, and collaborative content generation, its adoption is being stifled by infrastructural limitations, inconsistent policy practices, budget limitations, and staff skill shortages. Content diversification chances are promising, particularly in the realm of collaborative AI driven resource curation, policy convergence, and deliberate capacity building exercises. The study concluded that unlocking the power of AI requires a multi-pronged strategy that include investment in technology, policy reform, and retraining workers. The findings contributed to academic discussions on sustainable AI adoption in academic library consortia and provided actionable suggestions to policymakers, library administrators, and consortium members.