Every librarian I know has a secret list of tasks they wish someone else would handle.
Chasing duplicate records. Repeating subject headings. Pulling circulation statistics at midnight for yet another *National Assessment and Accreditation Council (NAAC)* report.
*Agentic AI might finally be that someone.*
Unlike a chatbot that simply answers a question and disappears, an AI agent can plan, use tools and carry a task through to completion. There is a difference between someone who gives you directions and someone who actually walks you to the door.
In a library, that journey could begin with the catalogue.
An AI agent could draft MARC records, check authority headings and prepare a batch for review before importing it into Koha. Another could extract metadata from a newly submitted thesis, prepare a DSpace record and flag relevant licensing requirements. A research assistant agent could search multiple databases, screen the results and prepare an annotated reading list while the librarian attends to other work.
Sounds promising? Certainly. But a little caution is necessary.
AI agents can invent citations, misinterpret licences and make mistakes with remarkable confidence. Librarians must therefore retain control over decisions involving acquisitions, record deletion, cataloguing and access to sensitive information.
Start with read-only access. Maintain an audit trail. Keep a human reviewer in the loop. And never send patron data to an external tool without appropriate privacy and security safeguards.
My suggestion is simple: don’t begin with a grand AI strategy.
Pick one repetitive task, perhaps metadata enrichment or new-arrival alerts. Run a small pilot with staff supervision. Measure the time saved, the errors introduced and the effort required to correct them. Then decide whether the agent deserves a bigger role.
Let the machine handle the chasing.
*The judgement, thankfully, still needs a librarian.*
Which library task would you hand over to an AI agent first?
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