A Multidimensional Assessment of AI Literacy Services in University Libraries

Abstract As artificial intelligence (AI) continues to reshape the landscape of higher education, academic libraries are emerging as strategic actors in advancing digital literacy and knowledge services. The rapid development of generative AI has transformed teaching, research, and scholarly communication, positioning libraries as pivotal hubs for supporting students, researchers, and educators in the responsible understanding, evaluation, and application of AI tools. In response, a growing number of universities have introduced AI-focused LibGuides that curate resources on literacy, ethics, research support, and pedagogical integration. To capture this phenomenon, the present study investigates the libraries of the world’s top 100 universities (QS World University Rankings), from which a representative sample of forty-nine universities was selected for in-depth analysis, selected for their leadership in teaching, research, and knowledge management, their early adoption of digital transformation, and their international diversity, which enables meaningful cross-regional comparison of institutional priorities and thematic emphases. Drawing on this sample, the research develops a multidimensional assessment framework incorporating indicators such as content relevance, resource integration, and service quality, and reveals significant variation in comprehensiveness, innovation capacity, and accessibility across institutions. Exemplars such as King’s College London, the University of Queensland, and the University of California, Los Angeles, demonstrate advanced practices in thematic curation, interdisciplinary organization, and user-centered service design. Building on these findings, the study proposes a conceptual model for AI literacy services grounded in collaborative knowledge ecology, emphasizing the co-participation of librarians, subject specialists, educators, and users in creating inclusive and pedagogically effective learning environments. By integrating empirical analysis with conceptual reflection, the research contributes to theoretical debates on the role of academic libraries in digital knowledge governance and provides actionable recommendations for optimizing AI-related service infrastructures, thereby supporting the equitable and sustainable integration of AI technologies in higher education.