Utilizing Large Language Models in Business ProcessManagement: Applications and Challenges

Abstract

Large Language Models (LLMs) have recently been used innumerous domains, such as Business Process Management (BPM), whichhas significantly advanced. With LLMs’ ability to understand language,reason, and tackle new challenges with minimal guidance, they offer anexciting opportunity to rethink and improve BPM practices. This systematic literature review examines insights from 42 peer-reviewed studies tounderst and how LLMs influence different stages of the BPM lifecycle. It sheds light on notable advancements and addresses the challenges that need to be overcome to unlock their full potential. Furthermore, we present aninteractive Streamlit application that demonstrates the practical application of LLMs across all five stages of the BPM lifecycle using zero-shotlearning, showcasing their potential to automate and enhance BPM tasks. We aim to deepen our understanding of the impact of LLMs on theevolution of BPM practices through a thorough review of current applications and future possibilities. The selected research papers coverLLM representation in various domains: process modeling (14%), process analysis and optimization (14%), process execution and monitoring (11%),process mining (19%), and generic capabilities and challenges (42%). Our findings underscore the growing importance of LLMs in addressing complex BPM scenarios while raising critical questions about scalability, interpretability, and fairness. Finally, this paper presents the technical, ethical, and practical challenges of integrating LLMs into BPM environments.