Artificial Intelligence Guardians: Smart Digital Preservation in Academic Libraries

Abstract

The growing volume of digital resources in academic libraries has intensified the need for sustainable preservation strategies. This study examined the extent of artificial intelligence (AI) application in digital preservation and its influence on the effectiveness of preservation strategies in academic libraries. A descriptive survey research design was adopted. The population comprised librarians and library personnel involved in digital preservation and information management across federal university libraries in Nigeria, from which a purposive sample of 31 respondents was drawn. Data were collected using a structured questionnaire. Descriptive statistics (mean and standard deviation) were used to answer the research questions, while Pearson correlation analysis was employed to test the relationship between AI application and digital preservation effectiveness at a 0.05 level of significance. The findings revealed a moderate level of AI application in digital preservation practices, with tools such as automated metadata generation and intelligent data management partially implemented. Digital preservation strategies were also found to be moderately effective. A significant positive relationship was established between AI application and preservation effectiveness, indicating that increased AI adoption enhances efficiency, accessibility, and sustainability of digital resources. However, major challenges identified include inadequate technical expertise, high cost of AI tools, infrastructural limitations, and lack of institutional policy support. The study recommends that academic libraries invest in AI-driven technologies, strengthen ICT infrastructure, and provide continuous training for librarians. It also emphasizes the need for institutional policies to guide the ethical and sustainable implementation of AI in library operations. This study provides empirical evidence on AI application and digital preservation effectiveness in academic libraries, contributing to the advancement of technology-driven preservation strategies in Library and Information Science.

Keywords: Artificial Intelligence, Digital Preservation, Academic Libraries, Machine Learning, Metadata Automation, Library and Information Science