Project Abstract

Abstract
The integration of artificial intelligence (AI) technologies in the field of library and information science has revolutionized the way academic libraries manage and develop their collections. This research project explores the utilization of AI for collection development in academic libraries, focusing on its impact, benefits, challenges, and implications. The study aims to investigate how AI can enhance the efficiency and effectiveness of collection development processes, leading to improved access to resources and better support for academic research and learning. Chapter 1 provides an introduction to the research topic, including the background of the study, problem statement, objectives, limitations, scope, significance, structure of the research, and definition of terms. Chapter 2 presents a comprehensive literature review covering ten key aspects related to AI in collection development, highlighting existing research, trends, and best practices in the field. The literature review examines how AI technologies such as machine learning, natural language processing, and data analytics are transforming collection development practices in academic libraries. Chapter 3 outlines the research methodology, detailing the research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter also discusses the selection criteria for AI tools and models used in the study, as well as the process for evaluating their effectiveness in supporting collection development activities. The methodology aims to provide a rigorous framework for investigating the impact of AI on collection development processes. In Chapter 4, the research findings are presented and discussed in detail, focusing on seven key areas identified during the study. The findings reveal the opportunities and challenges associated with implementing AI technologies in collection development, as well as the implications for library professionals, users, and stakeholders. The chapter examines how AI can facilitate the identification of relevant resources, improve metadata management, enhance user experience, and optimize resource allocation in academic libraries. Chapter 5 concludes the research project by summarizing the key findings, discussing their implications for practice and future research directions. The conclusion highlights the potential of AI to transform collection development practices in academic libraries, emphasizing the importance of collaboration, training, and ongoing evaluation of AI tools and models. The research contributes to the growing body of knowledge on AI applications in library and information science, providing insights into the opportunities and challenges of utilizing AI for collection development in academic settings. Overall, this research project offers valuable insights into the utilization of artificial intelligence for collection development in academic libraries, highlighting its potential to enhance resource discovery, access, and management. By exploring the impact of AI technologies on collection development processes, this study contributes to the ongoing conversation on the role of AI in shaping the future of academic libraries and information services.

Project Overview