# Generating Process Models by Interacting with Chatbots--A Literature Review
## 1 Introduction  
Process Modeling has been a fundamental component in the design and optimization of information systems for a long time, providing a framework for understanding and enhancing organizational processes. In the current era of digital transformation, process modeling faces the challenge of adapting to rapidly evolving technological landscapes [1]. The integration of chatbots, empowered by advancements in artificial intelligence (AI) and Natural Language Processing (NLP), particularly large language models, has the potential to revolutionize process modeling by enabling more intuitive and interactive ways of modeling business processes [2]. Interactive chatbots, equipped with the capability to understand and interpret human language, offer an intuitive and efficient means for various stakeholders to engage with process modeling. Chatbots can potentially streamline data collection, enable model updates, and facilitate user-friendly interactions (e.g., querying information from process models). This shift not only promises to make process modeling more accessible, but also aims to enhance the accuracy and relevance of models by capturing real-time inputs and diverse user perspectives. The relevance of this technology extends beyond simplifying the technical aspects of process modeling. In a broader context, it has the potential to significantly impact various fields, such as business process management, information systems, and organizational development. By automating and optimizing process model generation, organizations might achieve greater agility, better compliance, and enhanced operational efficiency. Furthermore, the democratization of process modeling through chatbots--meaning the creation of tools and techniques making the process ofprocess modeling more accessible to a broader range of people, regardless of their technical expertise--can lead to more inclusive and collaborative workplace environments.  
However, the integration of chatbots in process model generation comes with several challenges. Concerns regarding the accuracy of chatbot-generated models and issues of data security and privacy are paramount. In additions, concerns regarding the quality, correctness, and better comprehensibility of the generated process models, as well as a better collaboration between business process analysts and domain experts, are crucial. Through a comprehensive literature review, this paper investigates the current state of research in this domain, identifies gaps in the knowledge, and proposes pathways for future investigations. The aim is to provide a foundational understanding of the capabilities and limitations of integrating chatbots for generating process models, setting the stage for its evolution and effective implementation in various fields.  
The paper is structured as follows: In Section 2, the background and methodology of the systematic literature review (SLR) is described. Section 3 discusses the research questions we are interested in and the search strategy we adopted. In Section 4, the execution of the SLR is explained and an overview of the SLR results is presented. Section 5 presents the studies, followed by a discussion of the results in Section 6. Finally, Section 7 discusses threads to validity and Section 8 concludes the paper.