Toronto, ON -- April 2, 2026. BiblioCommons is advancing its exploration of artificial intelligence with a focus on what sets libraries apart: trust.

As AI adoption accelerates, public libraries are uniquely positioned to lead with an approach grounded in privacy, transparency, and community accountability. While large technology companies often prioritize scale and growth, libraries continue to center their work on public trust. This creates an opportunity to adopt AI in ways that strengthen, rather than erode, that relationship.

To explore this in practice, BiblioCommons partnered with four public libraries on a proof of concept examining how large language model (LLM) applications could support discovery and engagement. The initiative focused on technical feasibility, patron value, responsible AI use, and risk mitigation.

Three use cases were explored. The first focused on answering common patron questions using existing website content such as FAQs, events, and Hours & Locations. The system performed well on clear, factual queries, accurately identifying intent and returning source-backed responses. The results showed strong potential, with further improvements needed in response quality and content coverage.

The second explored AI-assisted discovery and readers' advisory. The system could distinguish between informational and transactional intent, helping patrons both learn about authors and find available titles. It performed well for both general queries and catalog searches. This work reinforced the importance of pairing AI with librarian expertise, with future exploration focused on incorporating staff-curated content and supporting discovery in context.

The third use case tested AI-generated summaries of patron comments. This proved to be the most consistent and immediately valuable application, producing accurate, neutral summaries supported by metadata. It shows strong potential for scaling across other forms of community-generated content.

Overall, the findings show that AI can be implemented in ways that align with library values. Focused applications deliver the strongest near-term value, while more open-ended experiences require further refinement. The differentiator is not the model itself, but the combination of trusted data, community context, and librarian expertise.

Building on these insights, BiblioCommons is exploring how AI can support the full patron journey, from initial search to final decision-making. Current areas of exploration include:

• Ask AI - Search and discovery support: Integrating AI into search to interpret more complex, exploratory queries and return meaningful results
• AI Guides - Contextual assistance: Providing relevant, guided prompts throughout the discovery experience
• AI Recommends - Personalized content promotion: Using anonymized interaction data and machine learning to surface relevant resources at the right moment
• AI Assists - Decision support: Helping patrons evaluate options and determine which materials, services and information are right for them

Early data shows that AI has the potential to transform the patron experience, moving from traditional search to a model where AI interprets user intent and assists patrons every step of the way. Across all efforts, the focus remains on enhancing the library experience while upholding the principles of privacy, access, and trust.

Connect with Us at PLA 2026

BiblioCommons is at PLA 2026 in Minneapolis, MN, at Booth #623. Visit us to see how this work is taking shape and to talk with our team about how AI can support discovery, engagement, and decision-making in your library.

About BiblioCommons

BiblioCommons builds software that transforms the public library's essential online services—catalog, mobile app, website, events calendar, and email marketing—from transactions to experiences worthy of the public library. BiblioCommons powers integrated online experiences for many of the top public libraries of all sizes across the United States and Canada.