Artificial intelligence tools for literature reviews: opportunities for academic libraries

Abstract

Purpose The rapid growth of scientific publications has increased the complexity of conducting literature reviews, making it more difficult for researchers to identify relevant studies and synthesize existing knowledge efficiently. Artificial intelligence (AI) technologies are increasingly being integrated into academic research workflows to support literature discovery, analysis and synthesis. This paper aims to explore how emerging AI-powered tools can support literature reviews and to examine the opportunities these technologies create for academic libraries to enhance research support services. Design/methodology/approach This paper adopts a conceptual and exploratory approach based on the analysis of emerging AI-based research tools used for literature discovery, citation analysis and knowledge synthesis. Several widely used platforms are examined to illustrate how machine learning and natural language processing technologies can support different stages of the literature review process. Findings The analysis indicates that AI-powered platforms can significantly improve literature discovery, accelerate research exploration and support evidence evaluation. Tools based on citation network analysis and generative AI can help researchers identify influential publications, explore research connections and organize knowledge more efficiently. Academic libraries can play an important role by integrating these technologies into research support services, offering training programs and promoting responsible AI use in scholarly communication. Originality This article contributes to the growing discussion on artificial intelligence in scholarly communication by highlighting practical opportunities for academic libraries to incorporate AI-powered tools into research support services and strengthen their role in the evolving digital research ecosystem.

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