The intelligent library: Thought leaders’ views on the likely impact of artificial intelligence on academic libraries
Open accessAbstract
Purpose: The last few years have seen a surge of interest in artificial intelligence (AI). The purpose of this paper is to capture a snapshot of perceptions of the potential impact of AI on academic libraries and to reflect on its implications for library work. Design/methodology/approach: The data for the study were interviews with 33 library directors, library commentators and experts in education and publishing. Findings: Interviewees identified impacts of AI on search and resource discovery, on scholarly publishing and on learning. Challenges included libraries being left outside the focus of development, ethical concerns, intelligibility of decisions and data quality. Some threat to jobs was perceived. A number of potential roles for academic libraries were identified such as data acquisition and curation, AI tool acquisition and infrastructure building, aiding user navigation and data literacy. Originality/value: This is one of the first papers to examine current expectations around the impact of AI on academic libraries. The authors propose the paradigm of the intelligent library to capture the potential impact of AI for libraries.
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This integrated workflow aligns with previous studies that emphasise the continuous data lifecycle, including curation, preservation, and reuse, as well as the collaborative and interconnected nature of research data services.
“This integrated workflow aligns with previous studies that emphasise the continuous data lifecycle, including curation, preservation, and reuse, as well as the collaborative and interconnected nature of research data services (Cox, Pinfield & Rutter, 2019;Pratama, 2025).”
From Librarians’ roles and responsibilities in managing data within academic libraries: A role-based data governance model (2026) · cites this paper as Cox, Pinfield & Rutter, 2019
In the concluding passage (section “!”, page unavailable), the paper identifies data management, curation and stewardship as potential library roles. The Library Manager passage also describes working with academics to create usable datasets. These passages support aspects of interconnected research-data services, but they do not set out a continuous data lifecycle encompassing preservation and reuse. (LLM, conf=0.84)
Experimental — accuracy not yet measuredPrevious studies confirm that libraries are increasingly adopting AI and related technologies, with librarians expected to complement rather than compete with these developments.
“Previous studies (Cox, 2022;Cox, Pinfield & Rutter, 2019;Noh, 2015) confirm that libraries are increasingly adopting AI and related technologies, with librarians expected to complement rather than compete with these developments.”
From Librarians’ roles and responsibilities in managing data within academic libraries: A role-based data governance model (2026) · cites this paper as Cox, Pinfield & Rutter, 2019
The background discussion (p. 3) says some AI applications have already reached academic libraries, but AI is only just coming into focus there and broader adoption was projected for the future. The discussion of librarians’ roles describes ways they might work with AI, while also warning of possible replacement of library staff; it does not establish that librarians will complement rather than compete with it. (LLM, conf=0.86)
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Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414 · see citing works
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727 · see citing works
Towards artificial intelligence-based assessment systems
Luckin, R. (2017) · Nature Human Behaviour · doi:10.1038/s41562-016-0028 · Cited by 303 · see citing works
Flagged first, then by citations
Research works printed but not linked: 11
- Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Giesinger Hall, C., Ananthanarayanan, V., Langley, K., and Wolfson, N. (2017). NMC Horizon Report: 2017 Library Edition. Austin, Texas: The New Media Consortium.
- Anderson, C. B., & Craiglow, H. A. (2017). Text mining in business libraries. Journal of Business & Finance Librarianship, 22(2), 149-165.
- Arlitsch, K., & Newell, B. (2017). Thriving in the age of accelerations: a brief look at the societal effects of artificial Intelligence and the opportunities for libraries. Journal of Library Administration, 57(7), 789-798.
- Dyas-Correia, S., & Alexopoulos, M. (2014). Text and data mining: Searching for buried treasures. Serials Review, 40(3), 210-216.
- Fernandez, P. (2016). "Through the looking glass: envisioning new library technologies" how artificial intelligence will impact libraries. Library Hi Tech News, 33(5), 5-8.
- Johnson, D. G., & Verdicchio, M. (2017). "AI Anxiety". Journal of the Association for Information Science and Technology, 68(9), 2267-2270.
- Neylon, C. (2012). More than just access: Delivering on a network-enabled literature. PLoS Biology, 10(10), e1001417. http://doi.org/10.1371/journal.pbio.1001417 · DOI
- Priem, J. (2013). Scholarship: Beyond the paper. Nature, 495(7442), 437-440. http://doi.org/10.1038/495437a · DOI
- Smith, A. (2016). Big Data Technology, Evolving Knowledge Skills and Emerging Roles. Legal Information Management, 16(4), 219-224.
- Tredinnick, L. (2017). Artificial intelligence and professional roles. Business Information Review, 34(1), 37-41.
- Vincze, J. (2017). Virtual reference librarians (Chatbots). Library Hi Tech News, 34(4), 5-8.
Cited by
Sorted by citations
Chatterjee, S., & Bhattacharjee, K. K. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10159-7 · Cited by 747 · see citing works
Artificial Intelligence in academic library strategy in the United Kingdom and the Mainland of China
Huang, Y., Cox, A. M., & Cox, J. (2023) · The Journal of Academic Librarianship · doi:10.1016/j.acalib.2023.102772 · Cited by 74 · see citing works
Self-citationWang, N., & Chou, Y. (2025) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.1518 · Cited by 4 · see citing works
Libraries and Artificial Intelligence
Rupar Korosec, M. (2021) · Advances in Library and Information Science · doi:10.4018/978-1-7998-7258-0.ch023 · Cited by 3 · see citing works
Peekhaus, W. (2026) · The Journal of Academic Librarianship · doi:10.1016/j.acalib.2025.103198 · Cited by 3 · see citing works
Akin-Fakorede, O. O., Ajani, Y. A., Adigun, O. M., & Malik, F. O. (2026) · Business Information Review · doi:10.1177/02663821261427234 · Cited by 2 · see citing works
Ayoib, A., Ismail, M. A., & Abdullah, N. (2026) · Malaysian Journal of Library and Information Science · doi:10.22452/mjlis.vol31no1.2
- Authors
- Cox, A. M., Pinfield, S., & Rutter, S.
- Affiliations
- University of Sheffield (GB)
- University of Leeds (GB)
- Venue
- Library Hi Tech
- Publisher
- Emerald
- Published
- 2019-09-16
- Volume
- 37
- Issue
- 3
- Pages
- 418-435
- ISSN
- 0737-8831 (ISSN-L)
- OpenAlex
- W2901672019
- Cited by
- 333
- References
- 3
- Citations by year
- 2026: 82 · 2025: 76 · 2024: 73 · 2023: 38 · 2022: 26 · 2021: 19 · 2020: 16 · 2019: 3
- FWCI
- 15.33
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Library Hi Tech (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Library Science and Information
- Physical Sciences › Computer Science › Information Systems › Web and Library Services
- Social Sciences › Library and Information Sciences › Library Science and Information Literacy
- Keywords
- artificial intelligence, academic libraries, intelligent libraries, scholarly publishing, learning, ethical considerations, data quality, job displacement, data curation, data literacy, library infrastructure
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