Purpose: Artificial intelligence (AI) has emerged as one of the most influential technologies of the twenty-first century, with far-reaching implications for industries, services, and research practices. In the field of library and information science, AI is increasingly viewed as a key enabler of innovation, operational efficiency, and user-centered service delivery. Academic libraries, as central knowledge infrastructures within higher education systems, have begun to adopt a wide range of AI-based tools and applications, including intelligent information retrieval systems, automated cataloging and classification, recommendation systems, chatbots, and data-driven decision-support mechanisms. These developments have the potential to transform traditional library functions and redefine the strategic role of academic libraries in teaching, research, and knowledge management. Despite the rapid expansion of scholarly publications in this area, existing studies are often fragmented and focus on specific technologies or localized applications, resulting in a limited understanding of the overall intellectual structure, thematic evolution, and research dynamics of AI in academic libraries. Addressing this gap, the present study provides a comprehensive scientometric analysis of the global research landscape on artificial intelligence in academic libraries.
Methodology: This study adopts a bibliometric and scientometric research design to systematically examine the development, structure, and trends of scholarly literature in this domain. Data were retrieved from the Scopus database, one of the most comprehensive and widely used indexing systems for peer-reviewed scientific publications. The dataset consists of 595 documents published between 1987 and 2025 that explicitly address artificial intelligence in the context of academic libraries. A long-term time span of thirty-eight years was selected to capture both early foundational studies and recent advances in the field. B