Adoption and Utilization of Artificial Intelligence in Academic Libraries

Challenges and Opportunities in Developed and Developing Nations

Abstract

Despite the significant potential that artificial intelligence (AI) holds for transforming academic libraries, various challenges have hindered its widespread adoption and use. As a result, AI integration in academic libraries remains limited, particularly in developed and developing countries. There is a lack of comprehensive reviews that explore the challenges and opportunities of AI adoption in academic libraries from a global perspective, comparing experiences across different regions.
Most existing studies focus on individual libraries, specific countries, or regions. This paper addresses that gap by examining the challenges and prospects of AI adoption in academic libraries in both developed and developing nations. Using desktop research and reviews of theoretical and empirical studies, 40 articles were analyzed, with 25 selected for the final evaluation. The paper identifies key barriers to AI adoption, including a lack of AI competencies and skills, limited knowledge and education on AI, resource constraints, ethical concerns, technological infrastructure gaps, fears of job loss, and the need for strategic planning.
It also explores the potential benefits of AI in academic libraries, such as applying expert systems for cataloging, classification, and indexing, using virtual agents for reference services, and enhanced surveillance capabilities. While the adoption of AI in academic libraries faces numerous obstacles, the future remains promising. The paper recommends that libraries, governments, and other stakeholders must actively work to address these challenges, paving the way for successful AI integration in academic libraries across the globe.