# BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AI

arXiv: https://arxiv.org/abs/2608.27149 · HTML: https://mlsanity.com/paper/2608.27149/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 39 references that are in the map.
- First posted on arXiv 27 Aug 2026.

## Builds on (most cited first, 7 of 7)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Large Language Models for Business Process Management: Opportunities and Challenges](https://mlsanity.com/paper/2304.04309/) (2023)
- [A Large Language Model Approach to Educational Survey Feedback Analysis](https://mlsanity.com/paper/2309.17447/) (2023)
- [Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration](https://mlsanity.com/paper/2212.06564/) (2022)
- [A Unified Conversational Assistant Framework for Business Process Automation](https://mlsanity.com/paper/2001.03543/) (2020)
- [Multipurpose Intelligent Process Automation via Conversational Assistant](https://mlsanity.com/paper/2001.02284/) (2020)
- [Comparing Generative Chatbots Based on Process Requirements](https://mlsanity.com/paper/2312.03741/) (2023)

## Abstract (arXiv)

Conversational AI systems, such as chatbots and virtual assistants, are becoming increasingly important to digital business processes. However, the established Business Process Model and Notation (BPMN) standard faces challenges when representing dynamic, context-sensitive interactions. This paper addresses this methodological and practical research gap by developing a standard-compliant BPMN extension (BPMN4CAI). Using Design Science Research methodology, this paper develops an approach that systematically extends existing BPMN elements and incorporates specialized components. The applicability and relevance of the BPMN4CAI framework are demonstrated and evaluated through a case study. The results show that the BPMN4CAI extension facilitates adaptive decision-making processes, robust context management, and transparent interactions for Conversational AI within business processes.