The incorporation of artificial intelligence (AI) into library services has garnered increasing attention in recent years, yet its practical implementation remains somewhat limited. Despite notable advancements, several critical aspects of library technical work, particularly classification and cataloguing, continue to heavily rely on manual processes. This paper examines challenges in current practices, notably the labour-intensive tasks of locating classification numbers and selecting subject headings. While the option to import MARC (machine-readable cataloguing) records via protocols like Z39.50 provides some relief, the absence of readily available records presents significant obstacles, especially for locally published materials. Against this backdrop, this research explores AI’s potential in generating relevant subject headings to streamline cataloguing processes and augment information retrieval efficiency. This study analysed hundred books from the Indian Institute for Human Settlements (IIHS) library, employing ChatGPT to generate subject headings. However, the resulting headings exhibited a lack of uniformity compared to manually catalogued entries. Library headings placed emphasis on geographic and physical details, whereas ChatGPT-generated headings were less detailed. Although ChatGPT facilitates instantaneous generation, the quality of headings varied, with some resembling MARC fields. Refinement of ChatGPT’s syntax could potentially enhance relevance. Despite its efficiency, ChatGPT cannot entirely replace the nuanced judgment required in manual cataloguing processes.