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AI-driven chatbots such as ChatGPT have caused a tremendous hype lately. ForBPM applications, several applications for AI-driven chatbots have beenidentified to be promising to generate business value, including explanation ofprocess mining outcomes and preparation of input data. However, a systematicanalysis of chatbots for their support of conversational process modeling as aprocess-oriented capability is missing. This work aims at closing this gap byproviding a systematic analysis of existing chatbots. Application scenarios areidentified along the process life cycle. Then a systematic literature review onconversational process modeling is performed, resulting in a taxonomy ofapplication scenarios for conversational process modeling, includingparaphrasing and improvement of process descriptions. In addition, this worksuggests and applies an evaluation method for the output of AI-driven chatbotswith respect to completeness and correctness of the process models. This methodconsists of a set of KPIs on a test set, a set of prompts for task and controlflow extraction, as well as a survey with users. Based on the literature andthe evaluation, recommendations for the usage (practical implications) andfurther development (research directions) of conversational process modelingare derived.

Conversational Process Modeling: Can Generative AI Empower Domain Experts in Creating and Redesigning Process Models?