Artificial Intelligence (AI) in Records Management in Academic Libraries: A Review

Abstract

Artificial Intelligence (AI) is increasingly transforming records management practices in academic libraries by introducing intelligent, automated, and data-driven approaches to managing records throughout their lifecycle. This review paper critically examines the application of AI technologies in records management within academic libraries, with particular attention to developing-country contexts. Drawing on contemporary scholarly literature, the paper explores key AI technologies—including machine learning, natural language processing, expert systems, robotic process automation, and predictive analytics—and their relevance to records creation, organization, storage, retrieval, preservation, and disposal. The review highlights the major benefits of AI adoption, such as improved operational efficiency, enhanced access to records, strengthened security, compliance with regulatory standards, and informed managerial decision-making. However, it also identifies critical challenges, including high implementation costs, inadequate infrastructure, skills deficits, ethical and privacy concerns, algorithmic bias, and resistance to organizational change. The paper concludes that while AI holds significant promise for revolutionizing records management in academic libraries, its successful implementation requires supportive policy frameworks, sustained funding, ethical governance, and continuous capacity building. Practical recommendations are offered to guide library administrators, policymakers, and information professionals toward sustainable and responsible AI integration.