AI in Libraries: Tools That Support Librarians in Research, Cataloging, and Accessibility

Lately, there’s been a lot of discussion about how artificial intelligence fits into an institution’s digital library. According to a recent study on research trends, 73.6% have used or are exploring AI tools for research. More people are turning to AI to help navigate the massive amount of information available today. While some worry it might replace the personal touch of a librarian, we see it differently. These tools are more like having a very fast assistant who never gets tired of sorting through data.

Here are a few ways AI in libraries is making daily tasks a little bit easier to handle.

1. Speeding Up Research and Discovery

Finding that one specific needle in a haystack of academic papers is a huge part of the job. Traditional search engines are great, but newer discovery tools can actually understand the context of a question.

• Zendy AI Discovery: This publisher-agnostic tool is specifically designed for library environments. It acts as a research partner, drawing only from trusted, peer-reviewed sources. It’s helpful because it guides students through their exploration rather than just giving them a list of links. Plus, it’s easy to add directly to a library’s existing digital portal.
• Consensus: This is a go-to for finding evidence-based answers. If a researcher asks a complex health or science question, Consensus searches through millions of research papers to give you a summary of what the experts actually say.
• Elicit: Can analyze thousands of papers at once, summarize the main findings, and even help you find related topics you might have missed.

2. Organizing the “Un-organizable”

Cataloging is the backbone of any library, but it’s time-consuming. AI in libraries can help with the heavy lifting of metadata, the behind-the-scenes info that makes books and files searchable.

• OCLC Record Manager: This tool uses AI to suggest classifications and subject headings based on the content of a book. It’s a huge help for clearing out cataloging backlogs.
• Annif: Developed by the National Library of Finland, this tool helps with automated indexing. It suggests subjects based on the text of a document, which helps librarians categorize digital collections much faster than doing it all by hand.
• Terentia: This is a platform designed for museums and libraries to help manage digital assets and ensure different systems can actually talk to each other.

3. Deepening Research on Accessibility

AI in libraries is becoming a vital part of research into removing barriers for researchers with diverse needs.

• Transcription Studies (Otter.ai or Whisper): These tools are being used to research how real-time transcription impacts learning. By transcribing guest speakers or workshops, librarians can study how providing a text version helps those who are hard of hearing or people who process information better through reading.
• Image Recognition Research: Modern tools can now “look” at an image and write a description for screen readers. Librarians are using these to audit their digital galleries, researching the best ways to describe complex visual data so that visually impaired patrons get the full story.
• Translation Tools: AI in libraries helps in researching the needs of non-native speakers. Tools like DeepL allow librarians to quickly provide translated guides, making it easier to see which community resources are most in demand.

4. Supporting Research and Information Literacy

One of the most valuable roles of a librarian is teaching others how to evaluate information. AI in libraries can be a great partner in showing students how to move from a broad idea to a focused research topic.

• Research Brainstorming (ChatGPT & Claude): Sometimes students come to the desk with a topic that is way too broad. You can use these tools as a sounding board to help them narrow it down. For example, asking for “5 different research angles for a paper on urban gardening” can give a student a concrete starting point.
• Source Evaluation Practice: Librarians can use AI to generate summaries or arguments on a topic and then work with students to fact-check those claims using library databases. It’s a hands-on way to teach “AI literacy” alongside traditional research skills.
• Visualizing Connections (ResearchRabbit): This tool maps out the relationships between different papers and authors. It’s a visual way to show a researcher how a specific conversation in their field has evolved over time.

Keeping a Human in the Loop

The most important thing to remember is that AI in libraries doesn’t have a “moral compass” or professional ethics, but librarians do. AI can get facts wrong or show bias, so it still takes a human expert to double-check the work and make sure the information being shared is accurate and fair.

At the end of the day, these tools are just another set of resources to help you do what you’ve always done: connect people with the stories and information they need.