Re-Engineering School Library Funding and Utility in Nigeria through Data Analytics and AI Driven Smart Hubs

Abstract: The global transition towards smart education necessitates a fundamental redefinition of school libraries, transforming them from passive repositories into dynamic, data-informed knowledge centres. In Nigeria, this transformation faces persistent challenges, including chronic underfunding, inadequate infrastructure, uneven policy implementation, and a misalignment between library services and the learning needs of digitally oriented students. This paper contends that sustainable school librarianship requires the strategic adoption of data analytics and artificial intelligence (AI) to enhance institutional relevance, funding resilience, and measurable educational value. Drawing on peer-reviewed and policy literature published between 2016 and 2026, the study develops a conceptual framework for reengineering Nigerian school libraries into AI-enabled Smart Knowledge Hubs tailored for resource-constrained environments. The paper introduces predictive funding models that enable school librarians to leverage usage data, literacy indicators, digital engagement metrics, and learning outcomes to demonstrate value and guide funding decisions. It also presents a low-bandwidth Smart Knowledge Hub model that emphasizes open educational resources, offline-first access, personalized learner support, ethical AI, and networked connections over mere collections. The study recommends that school libraries in Nigeria should be redefined to position librarians as data-informed knowledge strategists capable of using data analytics and AI to enhance teaching, learning, and educational inclusion. Data analytics and AI should be integrated as core strategic tools for advocacy, accountability, and improved decision-making within the smart school ecosystem, supported by adequate policy, training, and infrastructure. Keywords: artificial intelligence, knowledge hubs, predictive funding, school librarianship.