Generative AI for BPMN Process Analysis: Experiments with Multi-modal Process Representations

Advocating a convergence between generative AI and BPMN-based process analysis, this study reports on experiments with multi-modal business process representations. By leveraging the capabilities of the Bee-Up modeling tool for RDF serialization and the standard XML export of SAP Signavio, the report probes into the generative AI ability of BPMN interpretation according to these different serializations. In addition, the deployment of multi-modal AI – that directly processes image inputs – transcends traditional constraints of machine readability of BPMN diagrams. For prompt engineering, we employ a combined strategy utilizing semantic processing offered by Ontotext GraphDB integrated with LLM services from OpenAI, which, applied on RDF representations of BPMN, can push the boundaries of natural language interactions with visual process models. The investigation experiments with the interpretation of BPMN process models through such AI-based user interactions, highlighting possibilities of integrating conversational AI with the Business Process Management lifecycle. Assessments of outcomes are based on the RAGAs framework.