Literature Reviews with Llm-Based Tools

Abstract

The integration of large language models (LLMs) into academic research represents a potential change in how research engages with existing knowledge. While literature reviews have served as a significant means of passing on academic research, the exponential growth of output has created an unsustainable burden. No one can read it all; far too much of it is repetitive and unoriginal. The time needed to engage in meaningful fieldwork is endangered. This paper examines how LLM integration can aid research practice by automating aspects of literature synthesis, freeing up time for experiential investigation and theory development. Through analysis of emerging practices, we highlight how technological augmentation can create space for engagement with the empirical, while maintaining rigor and relevance. We demonstrate our position via an exemplary case and its analysis. We will suggest that thoughtful LLM integration can address a critical tension in organizational studies: maintaining awareness of existing scholarship while fostering engagement with living organizational reality.

Keywords: Large Language Models, Literature Review, Research Methods, Fieldwork, Experiential Research, Research Policy