Biblios: building an AI-powered chatbot for library resource discovery – a practitioner case study

Abstract

Purpose This paper aims to explore the potential of artificial intelligence (AI)-powered chatbots to enhance the resource discovery systems by addressing the limitations of online public access catalogs (OPACs). It examines how AI chatbots can provide more intuitive and personalized resource discovery for library users. Design/methodology/approach The study uses pilot study approach to analyze the effectiveness of an AI chatbot named Biblios. Biblios was trained on metadata of 50 books available on a private University Library in Bangladesh. Findings The paper finds that AI-powered chatbots can significantly enhance resource discovery by understanding complex user needs. The integration of these tools allows for a more personalized and efficient user experience in library settings. Originality/value This work contributes to the field of virtual librarianship by synthesizing current AI capabilities with traditional library services, providing a roadmap for the transformation of academic libraries through AI integration.

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