The Impact of Artificial Intelligence on Revolutionizing Metadata Management: Perspectives on Challenges, Prospects, and New Trends

Abstract

This paper investigates the use of artificial intelligence (AI) in metadata management in libraries,
focusing on the problems, potential, and future improvements. Metadata is critical for organizing,
managing, and retrieving library resources, and AI has the potential to automate these processes.
The study's major goals are to investigate the issues libraries face when implementing AI-based
metadata systems, find potential for improving metadata procedures, and assess new trends in this
field. A thorough literature study was used to examine important scholarly publications and glean
useful insights. The findings indicate that data quality issues, ethical concerns, and technical
constraints are the primary challenges facing libraries. At the same time, AI offers substantial
opportunities, including automated metadata generation, improved resource discoverability, and
efficient management of large digital collections. Predictive analytics and linked data adoption are
predicted to increase in the future, which will have a big impact on metadata management
procedures. The study concludes that although AI delivers considerable advantages, human
supervision remains critical, and libraries must prioritize staff training and policy updates to ensure
successful AI integration.