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Large Language Models for Business Process Management: Opportunities and Challenges

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Business Process Management Forum (BPM 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 490))

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Abstract

Large language models are deep learning models with a large number of parameters. The models made noticeable progress on a large number of tasks, and as a consequence allowing them to serve as valuable and versatile tools for a diverse range of applications. Their capabilities also offer opportunities for business process management, however, these opportunities have not yet been systematically investigated. In this paper, we address this research problem by foregrounding various management tasks of the BPM lifecycle. We investigate six research directions highlighting problems that need to be addressed when using large language models, including usage guidelines for practitioners.

M. Vidgof and S. Bachhofner—Equal contribution.

This research received funding from the Teaming.AI project, which is part of the European Union’s Horizon 2020 research and innovation program under grant agreement No 957402. The research by Jan Mendling was supported by the Einstein Foundation Berlin under grant EPP-2019-524 and by the German Federal Ministry of Education and Research under grant 16DII133.

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Notes

  1. 1.

    See for example the OpenAI Cookbook GitHub repository, which provides code examples for the OpenAI API.

  2. 2.

    Rubber duck debugging.

  3. 3.

    See the ChatGPT failure archive (GitHub) for an up-to-date list.

  4. 4.

    https://openai.com/blog/chatgpt-plugins.

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Author information

Authors and Affiliations

  1. Vienna University of Economics and Business, Welthandelsplatz 1, 1020, Vienna, Austria

    Maxim Vidgof, Stefan Bachhofner & Jan Mendling

  2. Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany

    Jan Mendling

  3. Weizenbaum Institute, Hardenbergstraße 32, 10623, Berlin, Germany

    Jan Mendling

Authors
  1. Maxim Vidgof
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  2. Stefan Bachhofner
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  3. Jan Mendling
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Corresponding author

Correspondence to Maxim Vidgof .

Editor information

Editors and Affiliations

  1. University of Trento, Trento, Italy

    Chiara Di Francescomarino

  2. Technical University of Denmark, Kgs. Lyngby, Denmark

    Andrea Burattin

  3. TU Dortmund University, Dortmund, Germany

    Christian Janiesch

  4. The University of Queensland, Brisbane, QLD, Australia

    Shazia Sadiq

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Vidgof, M., Bachhofner, S., Mendling, J. (2023). Large Language Models for Business Process Management: Opportunities and Challenges. In: Di Francescomarino, C., Burattin, A., Janiesch, C., Sadiq, S. (eds) Business Process Management Forum. BPM 2023. Lecture Notes in Business Information Processing, vol 490. Springer, Cham. https://doi.org/10.1007/978-3-031-41623-1_7

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  • DOI: https://doi.org/10.1007/978-3-031-41623-1_7

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