AI adoption in academic libraries: Practices, challenges, and research opportunities

Abstract

Background: The integration of artificial intelligence (AI) into academic library operations represents one of the most consequential shifts in contemporary library science. Although AI adoption has accelerated globally, empirical evidence documenting actual practices, adoption barriers, and future research trajectories in Nigerian academic libraries remains sparse. This gap is consequential: without a systematic evidence base, institutional decision-makers and professional bodies are compelled to allocate resources and formulate strategy in an evidential vacuum. This study advances the field by delivering the first institutionally stratified empirical investigation comparing federal and state university libraries in Nigeria, thereby contributing a novel and contextually grounded perspective to the global discourse on AI adoption in library and information science.
Purpose: This study examines the current state of AI adoption in Nigerian academic libraries, identifying the technologies deployed, the challenges encountered across technological, organisational, environmental, and individual dimensions, and emerging directions for future scholarly inquiry.
Methods: A descriptive survey design was employed. Data were collected from 245 library professionals drawn from 30 purposively selected federal and state university libraries across Nigeria using a structured, validated questionnaire (Cronbach’s α = 0.87). Descriptive statistics and frequency distributions were used to analyse the data.
Results: Findings reveal that AI-powered catalogue search systems and chatbot-assisted reference services are the most widely adopted practices, while NLP tools and machine learning-based recommendation engines are gaining traction. Inadequate infrastructure, insufficient digital literacy, and limited funding constitute the most persistent barriers to adoption.
Conclusions: AI adoption in Nigerian academic libraries is at an early but promising stage, with significant variation across institutional types. The study concludes that targeted policy interventions, capacity-building initiatives, and sustained research investment are essential for scaling AI integration. These findings have direct implications not only for Nigeria but for the broader Global South library community seeking to navigate AI integration within resource-constrained environments.