Emerging research information practices in the era of generative artificial intelligence

Abstract In the context of artificial intelligence (AI)‐driven scientific research, research information practices are undergoing profound developments. This paper employs a mixed‐methods approach, combining topic modeling and interpretive content analysis, to explore emerging research information practices associated with the integration of generative AI into research. This study identifies six significant shifts: from keyword‐based search to prompt‐based retrieval, from human sensemaking to delegated interpretation, from human innovation to algorithmic co‐creation, from manual writing to generative authoring, from unregulated AI use to accountable disclosure, and from AI use to AI literacy. It further analyzes the implications of these emerging research information practices for research productivity, cognitive and critical thinking, academic integrity and ethics, and academic fairness. This study enriches existing research on information practices in evolving information environments and provides a practical path for researchers, libraries, publishers, universities, and research institutions to move beyond the simple use of AI toward the development of AI literacy.

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Publication Details

Journal
Journal of the Association for Information Science and Technology
Published
2026-10-28
DOI
https://doi.org/10.1002/asi.70124
Primary Topic
Library Science and Information
Type
article
Field-Weighted Citation Impact
0.00

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article

Emerging research information practices in the era of generative artificial intelligence

Loo Geok Pee, Xiaoguang Wang, Chaoxian Qin, Xiaojie Chen
4 links
Journal of the Association for Information Science and Technology
Library Science and Information
article

Emerging research information practices in the era of generative artificial intelligence

Loo Geok Pee, Xiaoguang Wang, Chaoxian Qin, Xiaojie Chen
article en

Abstract

Abstract In the context of artificial intelligence (AI)‐driven scientific research, research information practices are undergoing profound developments. This paper employs a mixed‐methods approach, combining topic modeling and interpretive content analysis, to explore emerging research information practices associated with the integration of generative AI into research. This study identifies six significant shifts: from keyword‐based search to prompt‐based retrieval, from human sensemaking to delegated interpretation, from human innovation to algorithmic co‐creation, from manual writing to generative authoring, from unregulated AI use to accountable disclosure, and from AI use to AI literacy. It further analyzes the implications of these emerging research information practices for research productivity, cognitive and critical thinking, academic integrity and ethics, and academic fairness. This study enriches existing research on information practices in evolving information environments and provides a practical path for researchers, libraries, publishers, universities, and research institutions to move beyond the simple use of AI toward the development of AI literacy.

Journal of the Association for Information Science and Technology
Nanyang Technological University (SG), Chinese Academy of Sciences (CN), Wuhan University (CN), Northwest Institute of Eco-Environment and Resources (CN)
National Social Science Fund of China
Openalex Percentile: Top 6%
Library Science and Information
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