Adopting Artificial Intelligence for digital transformation of University libraries: A review

Abstract

There’s a renewed focus on digital transformation (DT) of university libraries to become an intimate information center among emerging generations. Providing various user needs for different generations is a real challenge for a university library. Artificial Intelligence (AI) is one of the pivotal technological tools with the potential to digitally transform a university library. AI has the potential to enhance library services and operations, ultimately improving user experiences and promoting efficient resource management. The lacuna of having a comprehensive review regarding the use of AI in DT of university libraries will be addressed by this study. Thus, the objective of the research was to investigate how AI can have adopted to perform the DL of university libraries. The study is a literature review that was followed by the systematic literature review method. In achieving the purpose, related current empirical knowledge was searched and reviewed on “the use of AI in DT of university libraries” in the EBSCOhost, Lens.org, and Dimensions databases from 1946 (the age of baby boomers) to 2023 (present GenZ). The article selection criteria were executed using the PRISMA article selection flowchart steps. Bibliometric analysis will be performed using RStudio to achieve the research objectives. Literature reviled that; AI can be adopted for 1. Intelligent search and discovery, 2. Virtual assistants 3. Automated collection management, 4. Library management automation with data-driven decision-making options, and 5. For collaboration and building communities. Literature also suggests that the future university libraries will integrate with emerging technologies such as the Internet of Things (IoT), data analytics, and semantic web and lead towards enabling intelligent library systems, advanced recommendation engines, and personalized learning experiences. However, challenges such as ethical considerations, data privacy, algorithm bias, staff training, implementation cost, and user acceptance are critical factors that require careful attention while implementing AI solutions. Thus, more research and tested framework for the digital transformation of university libraries is highly essential before adopting AI into the university library systems.