Strategic Priorities for AI Integration and Digital Transformation in Academic Libraries

Abstract

This study develops a strategic framework for the integration of artificial intelligence and digital transformation in academic libraries to enhance knowledge management and user services in higher education. Employing a mixed-methods approach, the research analyzes strategic plans from the top 25 universities according to the Times Higher Education 2024 World University Rankings. Qualitative content analysis (validated by Cohen’s Kappa, κ = 0.737), Shannon entropy for component prioritization, and sensitivity analysis were used to identify key priorities and assess result stability. The findings reveal that digitization and digital preservation constitute the dominant strategic priority, followed by digital learning environments, open access initiatives, and data analytics. While interest in AI is growing, the implementation of advanced AI applications such as chatbots and intelligent agents remains limited. Key barriers include legacy infrastructures, ethical concerns (algorithmic bias, privacy, and transparency), and a shortage of AI skilled professionals’ challenges that are particularly acute in resource-constrained settings. The proposed scalable strategic framework adopts a phased approach: beginning with foundational digitization, advancing to data analytics and AI-powered services, and culminating in mature integration with strong ethical governance. This framework is specifically tailored for developing countries, offering contextual recommendations for academic libraries in Iran. By systematically mapping strategic priorities from leading institutions and integrating theoretical and practical dimensions, this study advances knowledge management theories particularly Nonaka’s SECI model and provides actionable guidance for library administrators seeking to build inclusive, intelligent, and sustainable academic libraries worldwide.