AI-Driven Innovation in Information Retrieval: Transforming Library Operations and User Engagement

This study explores the transformative potential of specific AI technologies, such as natural language processing, machine learning, and knowledge graphs, in redefining library operations and enhancing user engagement. An AI-based IR prototype integrating these technologies was developed and deployed in an academic library over three months. The system significantly improved search precision, recall, and user interaction metrics while streamlining library staff operations. User feedback highlighted increased satisfaction, ease of use, and trust in AI-assisted recommendations. These findings demonstrate the capability of these specific AI technologies to bridge the gap between traditional library models and future-ready, user-centric knowledge environments.