Agentic AI in Library and Information Science: Current Applications and Future Directions

Abstract

This article explores the rise and influence of agentic artificial intelligence systems within library and information science (LIS). Agentic AI characterized by autonomous decision-making, goal-directed behaviors, and interaction with the environment is transforming traditional LIS practices in areas such as collection management, information retrieval, and user services. The article synthesizes current implementations, including intelligent cataloging systems, personalized recommendation engines, autonomous reference assistants, and adaptive discovery platforms. These applications significantly enhance resource accessibility, metadata quality, and user engagement, while also raising important considerations around human-AI collaboration, information equity, and the evolution of professional roles. The article identifies key technological and ethical challenges facing LIS institutions adopting agentic systems, such as data quality concerns, algorithmic transparency, privacy preservation, and the evolving role of information professionals. This analysis provides a framework for libraries and information organizations to strategically incorporate agentic AI while preserving core professional values and enhancing their essential societal functions.