Nothing new under the sun: Agentic AI and the automated, connected catalog

The emergence of agentic AI is an important technology trend, and its implications for technical services librarianship have the potential to be profound. Agentic AI is introduced and distinguished from generative AI through its capacity to pursue goals, coordinate specialized agents, and carry out multi-step actions with limited human intervention. Current and prospective applications within technical services are examined, including in library service platforms (LSPs) as research assistants, and through the automation of metadata and the potential to enhance retrieval in digital environments. Concerns with regular large language models (LLMs) regarding transparency, bias, hallucinations, governance, accountability, data privacy, and the preservation of professional expertise are compounded in agentic AI environments where agents rely on LLMs. All told, agentic AI represents a continuation of historical patterns of technological change in libraries, and its effective adoption will depend on robust governance practices, ethical oversight, and sustained human expertise.

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Publication Details

Journal
Technical Services Quarterly
Published
2026-08-24
DOI
https://doi.org/10.1080/07317131.2026.2719143
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Nothing new under the sun: Agentic AI and the automated, connected catalog

C. Sean Burns, Heather Lea Moulaison, Nicole Darcy, Harold Jansen
Technical Services Quarterly
AI in Service Interactions
article

Nothing new under the sun: Agentic AI and the automated, connected catalog

C. Sean Burns, Heather Lea Moulaison, Nicole Darcy, Harold Jansen
article en

Abstract

The emergence of agentic AI is an important technology trend, and its implications for technical services librarianship have the potential to be profound. Agentic AI is introduced and distinguished from generative AI through its capacity to pursue goals, coordinate specialized agents, and carry out multi-step actions with limited human intervention. Current and prospective applications within technical services are examined, including in library service platforms (LSPs) as research assistants, and through the automation of metadata and the potential to enhance retrieval in digital environments. Concerns with regular large language models (LLMs) regarding transparency, bias, hallucinations, governance, accountability, data privacy, and the preservation of professional expertise are compounded in agentic AI environments where agents rely on LLMs. All told, agentic AI represents a continuation of historical patterns of technological change in libraries, and its effective adoption will depend on robust governance practices, ethical oversight, and sustained human expertise.

Technical Services Quarterly
University of Lethbridge (CA), University of Kentucky (US), University of Missouri (US)
Quality Education
Openalex Percentile: Top 8%
AI in Service Interactions
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