The Journal of Academic Librarianship· 2026Q1
The role of AI in academic library reference services: A bibliometric analysis
- 0citations
- Q1SCImago
- 2026year
Short summary
Research on AI in academic library reference services shows a clear upward trend, peaking in 2025, with the US, China, India, and Pakistan leading publications.
AI-generated from the title and abstract; the full text is not read.
Key points
- Research output on AI in academic library reference services shows a general upward trend, peaking in 2025.
- The United States, China, India, and Pakistan are the leading countries in publication volume.
- Key thematic clusters include general AI in libraries, information literacy, generative AI, and AI literacy.
- Author collaboration is concentrated among a few highly connected individuals, and geographic participation is uneven.
AI-generated from the title and abstract; the full text is not read.
Abstract
The integration of artificial intelligence (AI) into academic library reference services has emerged as a significant area of scholarly interest. Using bibliometrix in R and VOSviewer, this study examines publication trends, identifies leading journals, countries, and authors, maps thematic clusters through keyword co-occurrence analysis, and examines author collaboration and co-citation patterns. The findings show a general upward trajectory in research output, with a peak in 2025. The United States, China, India, and Pakistan lead in publication volume, while the Journal of Academic Librarianship and Library Hi Tech News are the most prominent outlets. Thematic analysis reveals that the literature is anchored by a well-established core centered on artificial intelligence and academic libraries generally, alongside a closely related and increasingly central cluster covering information literacy, generative AI, and AI literacy. More specialized applications, including large language models, research data management, and library automation, are well-developed but remain comparatively narrow in scope. The author collaboration network is concentrated among a small number of highly connected authors, and co-citation patterns point to an intellectual structure that is still taking shape, consistent with the relatively short time span this literature covers. Geographic participation also remains uneven, with contributions concentrated in a handful of countries. These findings provide a structured foundation for future research and offer practitioners a clearer picture of where knowledge in this domain currently stands, along with where the evidence base for applying AI beyond chatbot services is still thin.
The authors' abstract, as published at the source. The Journal of Academic Librarianship, 2026 · DOI ↗
The rest is in the Pofolia app
Takeaways and questions to the paper; new summaries every day for your field. Free.
Sign in on the web to openStatistics, Probability and UncertaintyDecision Sciences