Large Language Models and the Future of Organization Theory

Joep Cornelissen*, Markus A. Höllerer, Eva Boxenbaum, Samer Faraj, Joel Gehman

*Corresponding author for this work

Research output: Contribution to journalEditorialpeer-review

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Abstract

In this editorial essay, we explore the potential of large language models (LLMs) for conceptual work and for developing theory papers within the field of organization and management studies. We offer a technically informed, but at the same time accessible, analysis of the generative AI technology behind tools such as Bing Chat, ChatGPT, Claude and Gemini, to name the most prominent LLMs currently in use. Our aim in this essay is to go beyond prior work and to provide a more nuanced reflection on the possible application of such technology for the different activities and reasoning processes that constitute theorizing within our domain of scholarly inquiry. Specifically, we highlight ways in which LLMs might augment our theorizing, but we also point out the fundamental constraints in how contemporary LLMs ‘reason’, setting considerable limits to what such tools might produce as ‘conceptual’ or ‘theoretical’ outputs. Given worrisome trade-offs in their use, we urge authors to be careful and reflexive when they use LLMs to assist (parts of) their theorizing, and to transparently disclose this use in their manuscripts. We conclude the essay with a statement of Organization Theory’s editorial policy on the use of LLMs.
Original languageEnglish
JournalOrganization Theory
Volume5
Issue number1
Number of pages15
ISSN2631-7877
DOIs
Publication statusPublished - Jan 2024

Keywords

  • AI technology
  • ChatGPT
  • Large language models
  • LLM
  • Organization theory

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