Exploring the scope of generative AI in literature review development

Guido Schryen (), Mauricio Marrone () and Jiaqi Yang ()
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Guido Schryen: Paderborn University
Mauricio Marrone: Macquarie University
Jiaqi Yang: Macquarie University

Electronic Markets, 2025, vol. 35, issue 1, No 13, 26 pages

Abstract: Abstract Artificial intelligence (AI) has the potential to transform the way research is conducted, particularly through generative AI (GenAI) tools which can enhance written communication and foster innovation via knowledge development. This study focuses on the latter, examining the role of GenAI in specific knowledge development activities within literature reviews. Through an epistemological lens, we distinguish six key knowledge development activities: research synthesis, evidence aggregation, critique, theory building, research gap identification, and research agenda development. Our analysis demonstrates both the capabilities and limitations of GenAI in supporting these activities, highlighting how GenAI can assist in synthesizing previous work, discovering and integrating concepts, and advancing various knowledge domains. We emphasize a human-centered, synergistic approach where GenAI complements researchers’ efforts, rather than replacing them. Additionally, our activity-centric analysis provides insights into how different types of literature reviews can effectively benefit from GenAI support, thereby contributing to a broader understanding of AI integration in information systems research.

Keywords: Generative AI; Literature reviews; Knowledge development; Innovation goal (search for similar items in EconPapers)
JEL-codes: M00 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12525-025-00754-2

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