Strategic Integration of Artificial Intelligence in Academic Libraries: A Global Analysis of Top-Ranked Universities

This study develops a strategic framework to integrate artificial intelligence (AI) into academic libraries, enhancing digital services and knowledge management in higher education. We analyzed strategic plans from the top 25 universities (Times Higher Education 2024 ranking) using a mixed-methods approach, combining qualitative content analysis (validated by Cohen’s Kappa, κ = 0.737), Shannon entropy for component prioritization, and sensitivity analysis to assess result stability. Findings reveal that 72% of universities prioritize digitization and preservation, 64% focus on AI-driven data analytics, and 48% emphasize open access, yet only 28% employ advanced AI tools like chatbots or search robots. Key barriers include incompatible legacy infrastructures, ethical concerns (e.g., algorithmic bias, privacy), and a shortage of AI-skilled professionals, particularly in developing countries like Iran. The proposed framework offers scalable strategies, including phased AI adoption, staff training, and ethical guidelines, tailored for resource-limited settings. This research advances knowledge management theories by systematically mapping AI priorities and provides practical guidance for library administrators to foster inclusive, data-driven libraries. By contextualizing global best practices, the study supports digital transformation in academic libraries worldwide, particularly in underrepresented regions.