Artificial Intelligence and Digital Transformation in Agricultural University Libraries: Current Trends, Challenges, and Future Directions

Vikash *

Department of Library & Information Science, Madhav University, Pindwara, Sirohi, Rajasthan, India.

Ajaya Kumar Saw

School of Library & Information Science, Gangadhar Meher University Sambalpur, Odisha, India.

Parmest Vishnu Kumar Sharma

College of Veterinary and Animal Science, Udaipur, India.

*Author to whom correspondence should be addressed.


Abstract

Agricultural university libraries support the research, teaching and extension mission of agricultural higher education, yet the integration of artificial intelligence (AI) into their services has not been systematically theorised or evidenced. This integrative review critically synthesises peer-reviewed articles, conference papers and authoritative institutional reports published between 2015 and 2026 on AI adoption and digital transformation in agricultural and allied academic libraries. Searches were conducted in Scopus, Web of Science Core Collection, AGRIS and CAB Abstracts and were supplemented by Google Scholar, citation chasing and the repositories of FAO, IFLA and UNESCO. Records were screened in two stages against explicit eligibility criteria, and the 64 sources synthesised were appraised by type and strength of evidence. The literature is structured along five application areas: intelligent discovery and semantic search based on agricultural vocabularies such as AGROVOC; automated metadata creation and cataloguing; conversational and virtual reference services, including generative AI assistants; research data management and institutional repositories; and AI-enabled knowledge transfer to extension professionals and farming communities. The synthesis indicates that adoption is uneven and largely experimental, limited less by the availability of technology than by infrastructural gaps, unstable funding, limited AI literacy among library professionals, unresolved privacy and copyright concerns, and the risk of inaccurate or fabricated AI outputs informing high-stakes agricultural decisions. Only seven of the sources deal specifically with agricultural libraries or their information infrastructure, and only two of these report primary empirical data, so evidence from India and other Global South contexts remains very limited. The review proposes a conceptual framework linking institutional readiness, responsible AI governance, librarian capacity development and equitable access to service outcomes for researchers, educators, students and extension personnel working in crop science, climate-resilient agriculture, biodiversity and food security. It offers a domain-specific synthesis largely absent from the library and information science literature, recasts agricultural university libraries as active intermediaries in agricultural knowledge and innovation systems rather than passive repositories, and outlines a prioritised agenda for empirical research, policy and practice.

Keywords: Artificial intelligence, generative AI, agricultural university libraries, digital transformation, semantic information retrieval, research data management, responsible AI governance, agricultural knowledge and innovation systems


How to Cite

Vikash, Ajaya Kumar Saw, and Parmest Vishnu Kumar Sharma. 2026. “Artificial Intelligence and Digital Transformation in Agricultural University Libraries: Current Trends, Challenges, and Future Directions”. Advances in Research 27 (6):323-40. https://doi.org/10.9734/air/2026/v27i61778.

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