Global Perspectives on AI-Driven Library and Information Services: Insights from India

Abstract Artificial intelligence (AI) is reshaping the global landscape of library and information services, with India’s diverse context offering valuable insights into international practices. This study synthesizes the evolution of AI in Indian library and information services, from early Integrated Library Systems like LIBSYS to advanced technologies, including machine learning, natural language processing, and predictive analytics. Employing a mixed-methods approach—a systematic review of over 60 sources, surveys of 75 libraries, interviews, and case studies of the National Digital Library of India, IIT Bombay Library, and a rural library in Uttar Pradesh—this study evaluates AI’s impact of AI on cataloguing, search efficiency, personalization, and accessibility. Key findings include an 85% AI adoption rate in urban libraries versus 20% in rural ones (M = 52%, SD = 12.5, p < 0.05), with case studies showing 35–45% improvements in efficiency metrics (e.g., query resolution time reduced by 45%, 95% CI [40%, 50%]). Visualizations, including pie charts, bar graphs, and tables, illustrate adoption trends, regional disparities, and barriers, such as the digital divide (affecting 55% of rural India, based on survey data), funding constraints, and ethical concerns, such as data privacy and algorithmic bias. By incorporating international comparisons (e.g., with China and the USA) and bibliometric trends, this study proposes strategies—public-private partnerships, digital literacy programs, ethical governance, and open-source solutions—to advance global library and information services in the post-pandemic world. This India-centric perspective contributes to the international scholarship on library development by emphasizing equitable technology adoption in multicultural settings. HIGHLIGHTS AI enhances global library and information services through multilingual cataloguing and semantic searches, with India’s diverse context providing key comparative insights. Empirical findings from 75-library survey show significant urban-rural disparities in AI adoption (t(73) = 5.1, p < 0.01), informing international equity strategies. Case studies demonstrate descriptive AI efficiencies, such as reduced query times, highlighting adaptable models for multicultural library practices. Ethical and infrastructural barriers emphasize the need for robust international governance in AI-driven information systems. India’s experiences offer evidence-based insights for sustainable global library transformation, advancing cross-cultural information access.