Agentic AI in library settings: a systematic literature review of prospects and challenges

The rapid development of agentic artificial intelligence is creating new possibilities for transforming library services from reactive models toward user-centered approaches. This systematic literature review (SLR) examines the prospects of agentic AI in library settings and identifies the key challenges associated with its effective and sustainable adoption. A systematic search was conducted using eight information sources that included ProQuest (LISA), EBSCOhost (LISTA), Scopus, Web of Science, Taylor & Francis, Emerald Publishing, ScienceDirect, and Google Scholar. The search retrieved 938 records, which were then screened, assessed for eligibility, and evaluated for quality. Through the systematic selection process, 15 studies were included in the final synthesis. The findings showed that agentic AI offers significant prospects for enhancing personalized reference and information services, automating routine library operations, supporting intelligent decision-making, improving user engagement, and facilitating proactive and responsive library services. However, its adoption is negatively affected by several challenges including funding limitations, skills gaps, data privacy concerns, ethical issues, algorithmic bias, inadequate infrastructure, and limited strategic leadership. The review reveals that successful adoption requires a human-centered approach that integrates technological capabilities with librarians’ professional expertise, appropriate governance mechanisms, continuous professional development, and organizational readiness. The study contributes to the emerging literature by systematically synthesizing evidence on both the prospects and challenges of agentic AI in library settings Practical recommendations are proposed for library leaders, practitioners, and policymakers to facilitate the effective integration of agentic AI into library services.