Considering the human factor in information systems is a key to future digitalization efforts, as stated in the Industry5.0 research and innovation actions of the EU. Especially in the design phase of a process-oriented information system, the human factor includes the empowerment of domain experts in process model creation lowering the entry hurdle for process modeling, and increasing modeling speed. In this work, we investigate how generative AI methods can support domain experts in creating process models in interaction with a chatbot based on textual process descriptions. We explore the amount of necessary information required as input to create process models with immediate visual representation using markdown-inspired languages and extend existing evaluation methods for assessing generated models, focusing on their completeness and correctness. Overall, an evaluation method has to consider the complex relationships between model completeness, correctness, textual process description, textual representation, and prompt engineering to support the domain expert.

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How Can Generative AI Empower Domain Experts in Creating Process Models?

  • Nataliia Klievtsova,
  • Juergen Mangler,
  • Timotheus Kampik,
  • Janik-Vasily Benzin,
  • Stefanie Rinderle-Ma

摘要

Considering the human factor in information systems is a key to future digitalization efforts, as stated in the Industry5.0 research and innovation actions of the EU. Especially in the design phase of a process-oriented information system, the human factor includes the empowerment of domain experts in process model creation lowering the entry hurdle for process modeling, and increasing modeling speed. In this work, we investigate how generative AI methods can support domain experts in creating process models in interaction with a chatbot based on textual process descriptions. We explore the amount of necessary information required as input to create process models with immediate visual representation using markdown-inspired languages and extend existing evaluation methods for assessing generated models, focusing on their completeness and correctness. Overall, an evaluation method has to consider the complex relationships between model completeness, correctness, textual process description, textual representation, and prompt engineering to support the domain expert.