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This paper introduces BPMN4CAI, an extension of the Business Process Model and Notation (BPMN) tailored for dynamic, context-sensitive interactions in conversational AI systems. By employing Design Science Research methodology, the authors systematically enhance existing BPMN elements and integrate specialized components to better model the complexities of conversational interactions. The case study results indicate that BPMN4CAI significantly improves adaptive decision-making, context management, and transparency in business process interactions involving conversational AI.
BPMN4CAI transforms how we model conversational AI, enabling adaptive decision-making and enhanced context management in business processes.
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.
