Open Access

Eva-Maria Schön, Jessica Kollmorgen, Michael Neumann, Maria Rauschenberger

• Context: Literature reviews play a critical role in the research process. They are used not only to generate new insights but also to contextualize and justify one’s own research within the existing body of knowledge. Problem: Since years, the number of scientific publications has been increasing rapidly. Therefore, conducting literature reviews can be time-consuming and error-prone. Objective: We investigate how integrating generative Artificial Intelligence (GenAI) tools may optimize the literature review process in terms of efficiency and methodological quality. Method: We conducted a single case study with 16 Master’s students at a University of Applied Science in Germany. They all carried out a Systematic Literature Review (SLR) using generative AI tools. Results: Our study identified use cases for the application of GenAI in literature reviews, as well as benefits and challenges. Conclusion: The results reveal that GenAI is capable of supporting literature reviews, especially critical parts such as primary study selection. Participants can scan large volumes of literature in a short time and overcome language barriers using GenAI. At the same time, it is crucial to assess GenAI outputs and ensure adequate quality assurance throughout the research process due to technology limitations, such as hallucination.