AI in automating library cataloging and classification

Purpose This paper aims to explore the role of artificial intelligence (AI) in automating library cataloging and classification processes, exploring current applications, challenges and future possibilities. It aims to provide insights into how AI technologies are reshaping traditional library practices and their implications for the future of information organization and access. Design/methodology/approach The paper presents a comprehensive review, analyzing recent research and developments in AI applications for library cataloging and classification. It covers traditional methods, relevant AI technologies, implementation challenges, impacts on library workflows and future directions. Findings AI technologies, particularly machine learning and natural language processing, offer significant potential for enhancing efficiency, consistency and depth in metadata creation and classification. However, implementation challenges include data quality issues, integration with legacy systems and the need for new skill sets among library professionals. The impact on library workflows is profound, necessitating a reimagining of traditional librarian responsibilities. Future developments promise more advanced capabilities in personalized discovery, adaptive classification schemes and predictive collection development. Originality/value This paper provides a holistic overview of AI’s impact on library cataloging and classification, synthesizing current research and future trends. It highlights the delicate balance required in leveraging AI to enhance library services while upholding core library values. The paper emphasizes the need for ongoing critical engagement with these technologies to shape the future of library services in the AI era.