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This study examines the integration of artificial intelligence (AI) into metadata management in libraries, focusing on its challenges, opportunities, and future trends. Metadata plays a critical role in organizing and retrieving library resources, and AI offers the potential to automate these processes. The objectives of this study are to explore the challenges libraries face with AI-driven metadata, identify opportunities for improvement, and analyze emerging trends. Using a systematic literature review, relevant articles were analyzed to draw insights. Key findings reveal that data quality, ethical concerns, and technical limitations are major challenges. However, AI presents opportunities such as automating metadata creation, improving resource discoverability, and efficiently managing large digital collections. Future trends include the increased use of linked data and predictive analytics, which will shape how metadata is managed. The study concludes that while AI brings significant benefits, human oversight is essential, and libraries need to focus on training staff and updating policies for effective AI integration.
Oyighan et al. (Thu,) studied this question.