Generative artificial intelligence (AI) has dazzled with its ability to create fluent language. However, its ability to read and analyze text remains under-appreciated. The text analysis ability offers the potential for libraries to engage in large-scale projects, like library assessment, that would otherwise be viewed as impractical due to the volume of information. Traditionally, analytics in libraries have focused on counting measurable items. This ranges from usage statistics, to instructional sessions count, etc. Generative AI offers the librarian the ability to go beyond these metrics and enrich analysis by including important values, such as accessibility and diversity. It also offers the ability to engage with text data at scale and for reasonable cost. This session explores how University of Hawaii at Manoa Natural Sciences librarian, Jonathan Young, and Humanities librarian Sarah Nakashima implemented automated and semi-automated AI methods to empower analysis in diverse areas, including reference, instruction, and collection development. The distinct projects enabled Hamilton library to provide services that were previously infeasible.
