Published Paper Details:

The Indian Library and Information Science (LIS) sector is experiencing a significant transformation, shifting from conventional rule-based classification systems such as the Dewey Decimal System and Colon Classification to AI-enhanced cognitive services that improve user discovery, automate metadata creation, and facilitate predictive and personalized information access. This research investigates the adoption of Artificial Intelligence (AI) and Machine Learning (ML) in Indian libraries, particularly in academic settings by analyzing national surveys, pilot initiatives, and policy documents. The study assesses current AI applications--including intelligent chatbot, multilingual OCR/NLP tools, and recommendation engines--while highlighting challenges related to professional skills, infrastructure, and ethical implementation. Additionally, the study addresses the deficiencies in LIS education and the lack of a cohesive policy framework for AI integration in libraries. Drawing on government initiatives like Digital India, NDLI, Indian, and NEP 2020, the paper provides actionable recommendations for incorporating AI/ML into LIS curricula, encouraging interdisciplinary collaboration, and fostering ethical, inclusive innovation in a multilingual environment. It establishes Indian libraries as crucial testing grounds for cognitive information services that support the country's goals of inclusive knowledge access and digital equity.