  AI-driven chatbots such as ChatGPT have caused a tremendous hype lately. For
BPM applications, several applications for AI-driven chatbots have been
identified to be promising to generate business value, including explanation of
process mining outcomes and preparation of input data. However, a systematic
analysis of chatbots for their support of conversational process modeling as a
process-oriented capability is missing. This work aims at closing this gap by
providing a systematic analysis of existing chatbots. Application scenarios are
identified along the process life cycle. Then a systematic literature review on
conversational process modeling is performed, resulting in a taxonomy of
application scenarios for conversational process modeling, including
paraphrasing and improvement of process descriptions. In addition, this work
suggests and applies an evaluation method for the output of AI-driven chatbots
with respect to completeness and correctness of the process models. This method
consists of a set of KPIs on a test set, a set of prompts for task and control
flow extraction, as well as a survey with users. Based on the literature and
the evaluation, recommendations for the usage (practical implications) and
further development (research directions) of conversational process modeling
are derived.
