AI Readiness in Libraries: A Technology–organization–environment framework for Action
Abstract
Many libraries have AI pilots, such as Chatbots and automated metadata pipelines, but librarians often feel unsure about integrating these tools into everyday service. This study presents preliminary results from an investigation into defining what “AI readiness” means for libraries. A systematic review and qualitative analysis of 46 publications, combined with five pilot interviews, yielded 145 open codes that were synthesized into a three-layer, fourteen-pillar framework. The technological layer emphasizes computing access, usable data, and a secure sandbox; the organizational layer encompasses explicit AI goals, leadership support, staff AI literacy, and clear guidelines; the environmental layer comprises privacy regulations, peer pressure, user feedback, public policy, and professional organization backing. Interviews revealed gaps in data quality, bias checks, and user feedback routines, while leadership engagement and a culture of small-scale experiments appear as key factors. Our next phase will include interviewing at least twenty additional librarians, developing survey instruments based on the framework, and testing interactions among pillars. The framework aims to serve as a practical checklist for library managers to evaluate AI readiness and identify areas needing development before committing resources to full AI deployment.
