Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring (Extended Abstract)

Kubrak, Kateryna; Botchorishvili, Lana; Milani, Fredrik; Nolte, Alexander; Dumas, Marlon

doi:10.24963/ijcai.2025/1213

Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring (Extended Abstract)

Kateryna Kubrak, Lana Botchorishvili, Fredrik Milani, Alexander Nolte, Marlon Dumas

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Sister Conferences Best Papers. Pages 10901-10905.

https://doi.org/10.24963/ijcai.2025/1213

Keywords

Sister Conferences Best Papers: Humans and AI
Sister Conferences Best Papers: Multidisciplinary Topics and Applications

Abstract

Prescriptive Process Monitoring (PrPM) systems recommend interventions in ongoing business process cases to improve performance. However, performance gains only materialize if users follow the recommendations. Prior research has shown that users are more likely to follow recommendations when they understand them. In this paper, we explore the use of Large Language Models (LLMs) to generate explanations for PrPM recommendations. We developed a prompting method based on typical user questions and integrated it into an existing PrPM system. Our evaluation indicates that LLMs can help users of PrPM systems to better understand the recommendations. The results indicate that LLMs can help users of PrPM systems to better understand the recommendations, and to produce recommendations that have sufficient detail and fulfill their expectations. However, the explanations fall short in addressing the underlying "why" and do not always support users in assessing the trustworthiness of the recommendations.

Kateryna Kubrak, Lana Botchorishvili, Fredrik Milani, Alexander Nolte, and Marlon Dumas. 2025. Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring (Extended Abstract). In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 10901–10905. https://doi.org/10.24963/ijcai.2025/1213

@inproceedings{ijcai2025p1213,
  title     = {Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring (Extended Abstract)},
  author    = {Kubrak, Kateryna and Botchorishvili, Lana and Milani, Fredrik and Nolte, Alexander and Dumas, Marlon},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {10901--10905},
  year      = {2025},
  month     = {8},
  note      = {Sister Conferences Best Papers},
  doi       = {10.24963/ijcai.2025/1213},
  url       = {https://doi.org/10.24963/ijcai.2025/1213},
}

TY  - CPAPER
TI  - Explanatory Capabilities of Large Language Models in Prescriptive Process Monitoring (Extended Abstract)
AU  - Kubrak, Kateryna
AU  - Botchorishvili, Lana
AU  - Milani, Fredrik
AU  - Nolte, Alexander
AU  - Dumas, Marlon
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 10901
EP  - 10905
DO  - 10.24963/ijcai.2025/1213
UR  - https://doi.org/10.24963/ijcai.2025/1213
ER  -