Authors :
Dr. Dharmishtha Dangar
Volume/Issue :
Volume 11 - 2026, Issue 8 - August
Google Scholar :
https://tinyurl.com/3rtf2cvt
Scribd :
https://tinyurl.com/52e3chmn
DOI :
https://doi.org/10.38124/ijisrt/26aug304
Note : A published paper may take 4-5
working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and
ResearchGate.
Abstract :
Artificial Intelligence (AI) is transforming academic libraries by enabling intelligent, efficient, and user-centred
services. Although technologies such as Radio Frequency Identification (RFID), mobile applications, recommendation
systems, predictive analytics, and conversational agents have been adopted in many libraries, their implementation often
remains fragmented. This conceptual paper proposes an AI-Informed Intelligent Library Circulation Concept (AI-ILC) that
integrates these technologies into a unified service-oriented framework. Unlike technology-driven approaches, the proposed
concept positions AI as a decision-support tool that complements librarians' expertise while enhancing user experience,
operational efficiency, and evidence-based management. The model consists of five interconnected components: intelligent
user access, intelligent circulation services, decision support, personalized user engagement, and continuous service
improvement. The paper contributes to the growing discourse on AI-enabled academic libraries by providing a strategic
conceptual framework for modernizing circulation services while preserving the professional values of librarianship,
including privacy, accessibility, transparency, and equitable access. It further identifies future research opportunities for
empirical validation and practical implementation in higher education institutions.
Keywords :
Artificial Intelligence, Academic Libraries, Library Circulation, Smart Libraries, Intelligent Library Services, UserCentred Services.
References :
- American Library Association. (n.d.). Facial recognition. Retrieved from https://www.ala.org/future/trends/facialrecognition
- Almulla, A., Alharbi, F., & Alshammari, M. (2026). AI-driven personalization in library and information services: A systematic review of techniques, user outcomes, and ethical considerations. The Journal of Academic Librarianship, 52(1), 103195. https://doi.org/10.1016/j.acalib.2025.103195
- Asim, M., Arif, M., & Rafiq, M. (2022). Applications of Internet of Things in university libraries of Pakistan: An empirical investigation. The Journal of Academic Librarianship, 48(6), 102613.
- Butters, A. (2008). RFID in Australian academic libraries: Exploring the barriers to implementation. Australian Academic & Research Libraries, 39(3), 198–206.
- Chelliah, J., Sood, S., & Scholfield, S. (2015). Realising the strategic value of RFID in academic libraries: A case study of the University of Technology Sydney. The Australian Library Journal, 64(2), 113–127.
- Cox, A. M., Pinfield, S., & Rutter, S. (2019). The intelligent library: Thought leaders' views on the likely impact of artificial intelligence on academic libraries. Library Hi Tech, 37(3), 418–435. https://doi.org/10.1108/LHT-08-2018-0105
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- Harisanty, D., Anna, N. E. V., Putri, T. E., Firdaus, A. A., & Azizi, N. A. N. (2025). Is adopting artificial intelligence in libraries urgency or a buzzword? A systematic literature review. Journal of Information Science, 51(2), 511–522.
- Kharat, S., Nagarkar, S., & Panage, B. (2023). A systematic literature review (SLR) of circulation methods in academic libraries: Proposing QR codes for self-issue/return method. Global Knowledge, Memory and Communication, 74(3/4), 845–863. https://doi.org/10.1108/GKMC-08-2022-0188
- Oakleaf, M. (2010). The value of academic libraries: A comprehensive research review and report. Chicago, IL: Association of College and Research Libraries.
- Okunlaya, R. O., Syed Abdullah, N., & Alias, R. A. (2022). Artificial intelligence library services: Innovative conceptual framework for the digital transformation of university education. Library Hi Tech, 40(6), 1869–1892.
- Reinsfelder, T. L., & O'Hara-Krebs, K. (2023). Implementing a rules-based chatbot for reference service at a large university library. Journal of Web Librarianship, 17(4).
- Rubin, V., Chen, Y., & Thorimbert, L. (2010). Artificially intelligent conversational agents in libraries. Library Hi Tech, 28(4), 496–522.
- Wang, X., Wu, Y. C., Zhou, M., & Fu, H. (2024). Beyond surveillance: Privacy, ethics, and regulations in face recognition technology. Frontiers in Big Data.
Artificial Intelligence (AI) is transforming academic libraries by enabling intelligent, efficient, and user-centred
services. Although technologies such as Radio Frequency Identification (RFID), mobile applications, recommendation
systems, predictive analytics, and conversational agents have been adopted in many libraries, their implementation often
remains fragmented. This conceptual paper proposes an AI-Informed Intelligent Library Circulation Concept (AI-ILC) that
integrates these technologies into a unified service-oriented framework. Unlike technology-driven approaches, the proposed
concept positions AI as a decision-support tool that complements librarians' expertise while enhancing user experience,
operational efficiency, and evidence-based management. The model consists of five interconnected components: intelligent
user access, intelligent circulation services, decision support, personalized user engagement, and continuous service
improvement. The paper contributes to the growing discourse on AI-enabled academic libraries by providing a strategic
conceptual framework for modernizing circulation services while preserving the professional values of librarianship,
including privacy, accessibility, transparency, and equitable access. It further identifies future research opportunities for
empirical validation and practical implementation in higher education institutions.
Keywords :
Artificial Intelligence, Academic Libraries, Library Circulation, Smart Libraries, Intelligent Library Services, UserCentred Services.