Research on AI-driven innovations and services in academic libraries: A bibliometric and systematic literature review

ABSTRACT Purpose This study aims to analyze academic research on Artificial Intelligence (AI) applications and tools in academic libraries, focusing on publications from the Scopus database between 2014 and 2024. Design/methodology/approach The study adheres to the PRISMA protocol, using VOSviewer, Bibliometrix, and Rstudio’s Biblioshiny function for bibliographic analysis and visualization. Findings The study highlights how the potential of AI in academic libraries may be increased by changing user needs and technical advancements. It comprises four thematic clusters: foundational technologies (machine learning, natural language processing, and automation), emerging innovations (generative AI), user-centric applications (chatbots), and the importance of AI literacy. It also reveals research gaps in automation and strategic AI integration, providing recommendations for improving library services. Research limitations The study is limited to articles published between 2014 and 2024 in the Scopus database, potentially excluding previous foundational work and research from other sources. Practical implications The study offers policymakers and library practitioners insightful information on effectively utilizing AI tools. This may result in overlooking earlier foundational work and research from multiple sources. Originality/value The study discovers the role of artificial intelligence (AI) in modernizing academic libraries, identifying research gaps, and providing strategic insights to improve technology and user experience.

Authors

Institutions

Publication Details

Journal
Journal of Data and Information Science
Published
2025-06-17
DOI
https://doi.org/10.2478/jdis-2025-0036
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on AI-driven innovations and services in academic libraries: A bibliometric and systematic literature review

Mayа Lambovska, Tipawan Silwattananusarn, Pachisa Kulkanjanapiban
1 citations
Journal of Data and Information Science
AI in Service Interactions
2.48
article

Research on AI-driven innovations and services in academic libraries: A bibliometric and systematic literature review

Mayа Lambovska, Tipawan Silwattananusarn, Pachisa Kulkanjanapiban
article en
1 citations

Abstract

ABSTRACT Purpose This study aims to analyze academic research on Artificial Intelligence (AI) applications and tools in academic libraries, focusing on publications from the Scopus database between 2014 and 2024. Design/methodology/approach The study adheres to the PRISMA protocol, using VOSviewer, Bibliometrix, and Rstudio’s Biblioshiny function for bibliographic analysis and visualization. Findings The study highlights how the potential of AI in academic libraries may be increased by changing user needs and technical advancements. It comprises four thematic clusters: foundational technologies (machine learning, natural language processing, and automation), emerging innovations (generative AI), user-centric applications (chatbots), and the importance of AI literacy. It also reveals research gaps in automation and strategic AI integration, providing recommendations for improving library services. Research limitations The study is limited to articles published between 2014 and 2024 in the Scopus database, potentially excluding previous foundational work and research from other sources. Practical implications The study offers policymakers and library practitioners insightful information on effectively utilizing AI tools. This may result in overlooking earlier foundational work and research from multiple sources. Originality/value The study discovers the role of artificial intelligence (AI) in modernizing academic libraries, identifying research gaps, and providing strategic insights to improve technology and user experience.

Journal of Data and Information ScienceVol. 10(4)
Prince of Songkla University (TH), University of National and World Economy (BG)
Quality Education
Openalex Percentile: Top 10%
AI in Service Interactions
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on AI-driven innovations and services in academic libraries: A bibliometric and systematic literature review — Mayа Lambovska, Tipawan Silwattananusarn, et al. · Journal of Data and Information Science (2025) | TGRS Research Map | TGRS