Building the AI-Driven Library of Tomorrow: Strategies and Perspectives
- DOI
- 10.2991/978-94-6463-712-0_3How to use a DOI?
- Keywords
- Artificial Intelligence; Information Retrieval; Metadata; Natural Language Processing (NLP); Neural Networks; Robotics
- Abstract
The integration of Artificial Intelligence (AI) is transforming college libraries from static repositories into dynamic, AI-enhanced environments that significantly improve user experience. AI technologies such as machine learning, natural language processing, and data analytics are redefining library functions by providing personalized support, streamlining research, and enhancing learning. This paper explores how AI-driven innovations are shaping the future of college libraries, making them more interactive, efficient, and adaptable to the needs of students, faculty members, and researchers. Moreover, it outlines the different types of machine learning, and their impact on library services, detailing the stages of AI integration, implementation challenges, and strategies to address them. It also covers evolving perspectives on AI and presents a model for the future AI-driven college library.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Abira Chakraborty PY - 2025 DA - 2025/05/15 TI - Building the AI-Driven Library of Tomorrow: Strategies and Perspectives BT - Proceedings of the International Conference on Marching Beyond the Libraries (ICMBL): Leadership, Creativity, and Innovation (ICMBL 2024) PB - Atlantis Press SP - 21 EP - 37 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-712-0_3 DO - 10.2991/978-94-6463-712-0_3 ID - Chakraborty2025 ER -