Enabling AI-Powered Creation of BPMN 2.0 Models
Business Process Management Notation (BPMN) plays a crucial role in optimizing organizational processes, yet creating accurate and adaptable models remains a challenge.
Nergiz, Serhat, 2025
Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Hinkelmann, Knut
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This research explores the integration of Generative Artificial Intelligence (GenAI) to automate the generation and refinement of BPMN 2.0 models directly from textual descriptions.
By leveraging natural language processing and generative transformers, the developed AI-driven tool simplifies the process modeling workflow, enhances precision, and reduces the dependency on BPM-specific expertise. The iterative refinement capabilities ensure adaptability to evolving business needs. Through design science research, this study evaluates the tool’s effectiveness in improving process accuracy, usability, and syntactic correctness, paving the way for more dynamic and efficient BPM practices.
This innovation aims to democratize BPMN modeling, making it accessible to non-experts while addressing critical challenges in process management.
Studiengang: Business Information Systems (Master)
Keywords Business Process Management, BPMN 2.0, Generative AI, Process Modeling, Artificial Intelligence
Vertraulichkeit: öffentlich