A Study on the Transformation of Subject Intelligence Service Models Driven by the AI4S Research Paradigm

Zhang Chao; Zhao Yanqiang

doi:10.13266/j.issn.0252-3116.2026.03.008

Library and Information Service >

2026 , Vol. 70 >Issue 3: 88 - 97

DOI: https://doi.org/10.13266/j.issn.0252-3116.2026.03.008

RESEARCH PAPERS

A Study on the Transformation of Subject Intelligence Service Models Driven by the AI4S Research Paradigm

Zhang Chao ,
Zhao Yanqiang

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1 National Science Library, Chinese Academy of Sciences, Beijing 100190;
2 Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
3 Wuhan Branch of the National Science Library, Chinese Academy of Sciences, Wuhan 430071;
4 Hubei Key Laboratory of Science and Technology Big Data, Wuhan 430071

Received date: 2025-07-15

Revised date: 2025-09-29

Online published: 2026-02-09

Supported by

This work is supported by the special project on literature and information capability building in Chinese Academy of Sciences, titled “Subject Intelligence Services for Scientific and Technological Innovation in Research Institutes” (Grant No. E4291103).

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Abstract

[Purpose/Significance] The AI for Science (AI4S) research paradigm is evolving rapidly, promoting scientific research toward increased intelligence, platformization, and interdisciplinary collaboration. This trend poses new challenges to traditional subject intelligence service systems, such as insufficient technological integration, lagging response mechanisms, and a misaligned capability structure. Clarifying the transformation direction of subject services under the AI4S paradigm is of great significance for building an efficient research support system. [Method/Process] This paper reveals the challenges and capability gaps faced by subject intelligence services under the AI4S research paradigm, designs a new AI4S-oriented subject intelligence service system around the data-information-knowledge-intelligence (DIKI) chain, and, based on transformations in research organizational forms, proposes paths for service content restructuring, subject librarian capability upgrading, and organizational mechanism innovation. [Result/Conclusion] The study concludes that driven by AI4S, subject intelligence services must shift from passive embedding to systemic collaboration and from reactive support to intelligent empowerment. Subject librarians should complete their role transformation by building core support capabilities in high-quality data curation, intelligent information output, and AI literacy. Meanwhile, service organizations must adapt to dynamic processes, reconfigure boundaries, and foster cross-domain collaboration to provide full-chain support for the intelligent research ecosystem.

Key words： AI4S; scientific research paradigm; subject intelligence; DIKI model

Cite this article

Zhang Chao , Zhao Yanqiang . A Study on the Transformation of Subject Intelligence Service Models Driven by the AI4S Research Paradigm[J]. Library and Information Service, 2026 , 70(3) : 88 -97 . DOI: 10.13266/j.issn.0252-3116.2026.03.008

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