Electronic Resources of University Libraries: AI-Driven Management and Optimization

Year : 2025 | Volume : 12 | Issue : 03 | Page : 8 15
    By

    Md. Tofazzol Hossain,

  • Kirna Kumari,

  1. Research Scholar, Department of Library and Information Science Guru Kashi University Talwandi Sabo, Punjab, India
  2. Assistant Professor, Department of Library and Information Science Guru Kashi University Talwandi Sabo, Punjab, India

Abstract

In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize user experiences. The management and optimization of ER in university libraries using AI is examined in this work. It explores important AI technologies that support intelligent indexing, metadata enrichment, and adaptive content distribution, including predictive analytics, natural language processing (NLP), and machine learning, and automated recommendation systems. Libraries can automate content curation, optimize resource allocation, and improve search capabilities to better serve the changing needs of researchers and students thanks to AI-powered tools. Additionally, by predicting resource demands, eliminating repetitive administrative duties, and evaluating consumption patterns, AI-integrated management systems improve operational efficiency. This guarantees a digital library environment that is more responsive and dynamic, which lowers bottlenecks and improves user happiness. The ability of chatbots and virtual assistants driven by AI to provide immediate support and direction is another example of how technology can revolutionize library services. Notwithstanding the apparent benefits, AI-driven electronic resource management has drawbacks as well, such as issues with data privacy, moral dilemmas, and the requirement for frequent system changes to guard against prejudice and guarantee inclusion. This paper identifies these issues and suggests tactical fixes for the long-term integration of AI in scholarly libraries. This paper attempts to give a thorough grasp of how AI is changing the administration of ER through a thorough analysis of existing methods and case studies from top academic institutions. The results highlight how important AI is to improve information retrieval, encouraging high-caliber research, and guarantee that academic libraries stay at the forefront of digital innovation. The study ends with tactical suggestions for academic stakeholders, library managers, and legislators to optimize the advantages of AI-driven solutions in efficiently managing ER.

Keywords: Electronic resources, artificial, intelligent, AI-integrated, utilization

[This article belongs to Journal of Advancements in Library Sciences ]

How to cite this article:
Md. Tofazzol Hossain, Kirna Kumari. Electronic Resources of University Libraries: AI-Driven Management and Optimization. Journal of Advancements in Library Sciences. 2025; 12(03):8-15.
How to cite this URL:
Md. Tofazzol Hossain, Kirna Kumari. Electronic Resources of University Libraries: AI-Driven Management and Optimization. Journal of Advancements in Library Sciences. 2025; 12(03):8-15. Available from: https://journals.stmjournals.com/joals/article=2025/view=234549


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Regular Issue Subscription Review Article
Volume 12
Issue 03
Received 20/08/2025
Accepted 10/09/2025
Published 22/09/2025
Publication Time 33 Days
161

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