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<p>Enterprise modeling (EM) typically includes multiple perspectives to analyze or design an organization, which is supposed to reduce the complexity of the modeling process and improve the structure of the resulting enterprise models. However, for non-modeling experts, i.e., stakeholders without solid training in EM, the development and integration of different model perspectives remains a challenge. Based on previous research in conceptual modeling, the paper investigates the use of large language models (LLMs) to support non-modeling experts of multi-perspective EM. Positioned in the roadmap for increasing the reach of EM, an LLM-based toolchain and reusable prompts for generating multi-perspective enterprise models from textual descriptions are proposed and evaluated. The results indicate that LLMs can be seen as assistive technology for certain tasks in EM. The main contributions of the paper are (1) an analysis of the state of research in LLM use in EM, (2) a study on LLM use for producing multi-perspective enterprise models, and (3) positioning LLMs in the roadmap for increasing the reach of EM.</p>

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LLM support for non-expert enterprise modeling

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月4日

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  • Peter-Alexander Kolev,
  • Hauke Hansen Pruss,
  • Jim Robert Wilken,
  • Benjamin Nast,
  • Kurt Sandkuhl

摘要

Enterprise modeling (EM) typically includes multiple perspectives to analyze or design an organization, which is supposed to reduce the complexity of the modeling process and improve the structure of the resulting enterprise models. However, for non-modeling experts, i.e., stakeholders without solid training in EM, the development and integration of different model perspectives remains a challenge. Based on previous research in conceptual modeling, the paper investigates the use of large language models (LLMs) to support non-modeling experts of multi-perspective EM. Positioned in the roadmap for increasing the reach of EM, an LLM-based toolchain and reusable prompts for generating multi-perspective enterprise models from textual descriptions are proposed and evaluated. The results indicate that LLMs can be seen as assistive technology for certain tasks in EM. The main contributions of the paper are (1) an analysis of the state of research in LLM use in EM, (2) a study on LLM use for producing multi-perspective enterprise models, and (3) positioning LLMs in the roadmap for increasing the reach of EM.