ADOPTION OF ARTIFICIAL INTELLIGENCE-DRIVEN LIBRARY SERVICES IN ACADEMIC LIBRARIES IN SOUTH-SOUTH NIGERIA

The study investigated the extent of Artificial Intelligence (AI) adoption in academic libraries in South-South Nigeria. It identified the types of AI tools currently in use, examined librarians' perceived benefits of AI-driven services, and the challenges constraining effective and strategic AI deployment in academic library environments. A mixed-methods research design was employed. Quantitative data were collected using a Four-Point Likert-Modified Rating Scale questionnaire administered to 100 professional librarians across six federal universities in South-South Nigeria. Qualitative data were obtained via semi-structured interviews with 12 ICT/system librarians. Descriptive statistics were used to analyze the data collected, while thematic analysis was used for the interview to complement and deepen quantitative findings. Findings revealed a low overall level of AI adoption (38.9%) in the studied academic libraries. Among available AI applications, plagiarism detection tools recorded relatively high usage, whereas advanced tools such as chatbots, predictive analytics, voice-based interfaces, and facial recognition technologies were minimally deployed. Respondents nonetheless reported high perceived benefits of AI adoption, including faster information access, improved user engagement, enhanced cataloguing accuracy, and stronger decision-support capabilities. Major challenges identified included inadequate ICT infrastructure, insufficient funding, shortage of skilled personnel, weak institutional AI policies, and technophobia among library staff. Qualitative evidence further showed that library services remain largely manual, with AI use being situational rather than strategically planned. The study concludes that despite strong perceived value and positive attitudes toward AI among librarians, effective adoption in academic libraries in South-South Nigeria remains limited by structural, financial, and capacityrelated constraints. To advance AI-driven library service transformation, the study recommends sustained investment in digital infrastructure, targeted human capital development, formulation of clear institutional AI implementation policies, and the establishment of sustainable funding mechanisms. These findings provide evidence-based guidance for innovation planning, technology investment, and digital readiness strategies in Nigerian academic libraries and comparable developing-country contexts.