Revolutionizing Library Cataloguing through Artificial Intelligence: A Critical Analysis
Keywords:
Artificial Intelligence, Library Cataloguing, Metadata Automation, Machine Learning, Annif, ChatGPT, Knowledge OrganizationAbstract
The rapid growth and changes in different types of information sources have challenged the effectiveness, accuracy, and ability of traditional library cataloguing processes to keep up. The artificial intelligence (AI) can provide new opportunities of overcoming these challenges due to automation processes, multilingual, and improved metadata generation. This project is a hybrid of both a systematic literature review (2018- 2025), and a practical application of AI-aided cataloguing using ChatGPT and Annif. The synthesis makes up the literature review that consists of international and local case studies on technological applicability, advantage, constraints, and ethics of AI in cataloguing. The experimental material compares the quality of AI-generated descriptive metadata and subject headings of print, digital and multilingual materials against human-made records, both in terms of accuracy and cultural sensitivity as well as time consumption.
The paper proposes a hybrid implementation model where an AI efficacy is upheld in combination with human vigilance to safeguard contextual precision and ethical integrity, and sustainable embrace. The staff training, ethical guidance, and investing in infrastructure are some of the strategic priorities. Such results give practical information that can guide library practitioners, system developers, and policymakers in the modernization of the practice of cataloguing while maintaining professional experience.
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