Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)

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AI-Enabled Information Retrieval in Libraries: Integration, Challenges, and Prospects

Authors
Hongzhuan Guo1, *
1The Library of Anhui Polytechnic University, Wuhu, 241000, China
*Corresponding author. Email: 44063598@qq.com
Corresponding Author
Hongzhuan Guo
Available Online 23 April 2026.
DOI
10.2991/978-94-6239-630-2_21How to use a DOI?
Keywords
Artificial Intelligence (AI); Library; Information Retrieval; Generative AI; Knowledge Acquisition; Intelligent Services
Abstract

With the rapid advancement of Generative Artificial Intelligence (AIGC) technology, large language models (LLMs) such as ChatGPT and DeepSeek are profoundly reshaping the ecosystem of information retrieval services in libraries. Drawing on multiple empirical studies and technical analysis literature, this paper systematically reviews the current application scenarios, technical pathways, and enabling mechanisms of AI in library information retrieval—focusing on typical practices like conversational AI-based reference consultation and personalized recommendation. It further analyzes core challenges across four dimensions: data security and privacy protection, algorithmic transparency and bias, technology adaptation and talent shortage, as well as user trust and ethical risks. Correspondingly, targeted development strategies are proposed, including the integration of the “Generative AI + Traditional Retrieval” hybrid model, strengthening data governance and ethical norm construction, improving librarians’ AI literacy and user information education, and exploring the application of federated learning and edge computing. These strategies aim to advance the intelligent and inclusive transformation of libraries, and build a credible human-AI collaborative service paradigm that balances technological empowerment with humanistic care.

Copyright
© 2026 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.

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Volume Title
Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)
Series
Advances in Computer Science Research
Publication Date
23 April 2026
ISBN
978-94-6239-630-2
ISSN
2352-538X
DOI
10.2991/978-94-6239-630-2_21How to use a DOI?
Copyright
© 2026 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

risenwbib
TY  - CONF
AU  - Hongzhuan Guo
PY  - 2026
DA  - 2026/04/23
TI  - AI-Enabled Information Retrieval in Libraries: Integration, Challenges, and Prospects
BT  - Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)
PB  - Atlantis Press
SP  - 211
EP  - 226
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-630-2_21
DO  - 10.2991/978-94-6239-630-2_21
ID  - Guo2026
ER  -