The Integration, Utility, and Ethical Challenges of Artificial Intelligence Tools in Academic Libraries

Abstract

Abstract Artificial intelligence has progressed from experimental trial to core operational infrastructure across contemporary academic libraries. Drawing upon peer-reviewed Library and Information Science (LIS) literature, ACRL and IFLA publications, and practitioner surveys from 2020 through 2025, this review examines the current deployment of AI technologies within information retrieval, metadata creation, reference triage, and patron analytics. Using Rogers' Diffusion of Innovations theory, the paper explains the marked disparities in institutional adoption rates across global higher education. Furthermore, an ethical governance lens highlights persistent challenges regarding algorithmic bias, data privacy, and citation hallucination. The analysis indicates a pronounced geographic and resource divide: well-funded research institutions in the Global North are rapidly transitioning librarians from traditional information intermediaries to educators of AI literacy and prompt design, whereas resource-constrained libraries face structural hurdles to adoption. To address these challenges, this study synthesizes an integrated operation–adoption–ethics framework, providing administrators, educators, and policy makers with a unified approach for responsible AI implementation alongside key directions for future empirical research.