Creating efficiencies when working with electronic resource records

This paper examines the challenges of managing electronic resource metadata at the University of Massachusetts Amherst Libraries (UMAL) following their migration to the FOLIO library services platform. Issues such as inconsistent deletion workflows, duplicated records in a single-tenant consortium environment, ambiguous “delete” data from OCLC Collection Manager, and the difficulty of mapping custom container codes to FOLIO identifiers created significant workflow inefficiencies. To address these problems, the eResources team used Microsoft Copilot, OCLC Knowledge Base APIs, and FSE FolioClient APIs to develop two Google Colab Jupyter Notebooks that automate title verification and identifier retrieval. These tools transformed previously manual, time-consuming processes into efficient batch operations, while still requiring human oversight for validation and metadata quality. The project highlights both the potential and the limitations of AI in library technical services—demonstrating efficiency gains, the importance of cross-department collaboration, and ongoing concerns about AI transparency and ethical use.