Application of Artificial Intelligence in Information Retrieval for Academic Research: A Systematic Literature Review Using PRISMA

Abstract

This study presents a systematic review on the integration of Artificial Intelligence (AI) in academic research, with particular emphasis on its applications, benefits, and challenges in information searching and retrieval. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 41 eligible articles published in 2024 were selected from Elsevier’s ScienceDirect and Google Scholar for analysis. The review reveals that AI’s role in academic research is closely linked to advancements in machine learning and data mining, particularly in the domain of information retrieval. Although the number of studies specifically addressing AI’s influence on academic research practices remains limited, findings indicate a growing interest in leveraging AI to enhance research methodologies and outcomes. A significant portion of the reviewed literature focuses on practical implementations of AI, especially machine learning, in academic libraries, highlighting AI’s potential to improve library operations and information services. Furthermore, the review identifies recurring themes around the benefits and limitations of AI in information retrieval, reflecting both opportunities and ongoing challenges in the field. Notably, research gaps were found in areas that explore the intersection of AI, information retrieval, and academic research practices, offering promising directions for future investigation. It is recommended that researchers further explore how AI can support innovative approaches in academic research, data analysis, and scholarly communication. Institutions such as libraries can leverage existing literature as a guide for adopting AI-driven tools to improve service delivery and research support.