Artificial Intelligence in Academic Libraries: An Analytical Study of Ethical Integration and Future Readiness in Indian Higher Education

Academic libraries in Indian higher education will undergo structural transition from collection-centered service models to digitally mediated, data-intensive and increasingly AI-enabled knowledge support systems. The present paper discusses how Indian academic libraries are integrating artificial intelligence ethically and how far they are ready for the future use of it. It also focuses on the AI-based reference services, discovery systems, automated metadata support, plagiarism detection, research analytics, learning analytics, automated user-support and more. A longitudinal study stipulated in Caribbean islands revealed that the cost of preventing activities could be reduced just by its plant or fertilizing of results that involve genetic or pathogenic obstructive 8 Dill's fathom and to plant resistance functional to different natural meritorious 7. The tool gauged their familiarity with AI, which included usage of any AI services, it then measured perceived usefulness of AI services, perception of ethical integration of AI, readiness of digital infrastructure, digital competency of librarian, future readiness of library and acceptance of AI-enabled library services. The application of descriptive statistics, reliability analysis, correlation analysis, one way ANOVA and multiple regression. The results of the simulation can be described as showing moderate to high AI awareness, more exposure to plagiarism and discovery tools than to conversations reference bots and a major ethical concern on privacy, transparency and algorithmic bias. As per regression analysis, AI awareness, perceived usefulness, ethical integration perception, digital infrastructure readiness and librarian digital competency together predict acceptance of AI-enabled library services. The paper argues that AI can benefit Indian academic libraries only when its adoption is complemented by policy safeguards and human intervention, along with transparent data governance, inclusive design, professional training and institutional investment. A study provides a governance-oriented framework for the adoption of responsible AI in academic libraries and suggests directions for future empirical research.