TY - GEN
T1 - Conversationally Actionable Process Model Creation
AU - Klievtsova, Nataliia
AU - Kampik, Timotheus
AU - Mangler, Juergen
AU - Rinderle-Ma, Stefanie
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - With the recent success of large language models, the idea of AI-augmented Business Process Management systems is becoming more feasible. One of their essential characteristics is the ability to be conversationally actionable, allowing humans to interact with the system effectively. However, most current research focuses on single-prompt execution and evaluation of results, rather than on continuous interaction between the user and the system. In this work, we aim to explore the feasibility of using chatbots to empower domain experts in the creation and redesign of process models in an effective and iterative way. In particular, we experiment with the prompt design for a selection of redesign tasks on a collection of process models from literature. The most effective prompt is then selected for the conducted user study with domain experts and process modelers in order to assess the support provided by the chatbot in conversationally creating and redesigning a manufacturing process model. The results from the prompt design experiment and the user study are promising w.r.t. correctness of the models and user satisfaction.
AB - With the recent success of large language models, the idea of AI-augmented Business Process Management systems is becoming more feasible. One of their essential characteristics is the ability to be conversationally actionable, allowing humans to interact with the system effectively. However, most current research focuses on single-prompt execution and evaluation of results, rather than on continuous interaction between the user and the system. In this work, we aim to explore the feasibility of using chatbots to empower domain experts in the creation and redesign of process models in an effective and iterative way. In particular, we experiment with the prompt design for a selection of redesign tasks on a collection of process models from literature. The most effective prompt is then selected for the conducted user study with domain experts and process modelers in order to assess the support provided by the chatbot in conversationally creating and redesigning a manufacturing process model. The results from the prompt design experiment and the user study are promising w.r.t. correctness of the models and user satisfaction.
KW - Conversations
KW - Large language models
KW - Process discovery
KW - Process improvement
KW - Process models
UR - http://www.scopus.com/inward/record.url?scp=85218932464&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-81375-7_3
DO - 10.1007/978-3-031-81375-7_3
M3 - Conference contribution
AN - SCOPUS:85218932464
SN - 9783031813740
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 39
EP - 55
BT - Cooperative Information Systems - 30th International Conference, CoopIS 2024, Proceedings
A2 - Comuzzi, Marco
A2 - Grigori, Daniela
A2 - Sellami, Mohamed
A2 - Zhou, Zhangbing
PB - Springer Science and Business Media Deutschland GmbH
T2 - 30th International Conference on Cooperative Information Systems, CoopIS 2024
Y2 - 19 November 2024 through 21 November 2024
ER -