2025
Integration of Process Mining and Large Language Models—Literature Review
HALAŠKA, Michal; Roman ŠPERKA; Radim DOLÁK and Tomáš BARČÁKBasic information
Original name
Integration of Process Mining and Large Language Models—Literature Review
Authors
Edition
Singapore, Smart Innovation, Systems and Technologies, p. 179-188, 10 pp. 2025
Publisher
Springer
Other information
Language
English
Type of outcome
Proceedings paper
Field of Study
50200 5.2 Economics and Business
Country of publisher
Singapore
Confidentiality degree
is not subject to a state or trade secret
Publication form
electronic version available online
References:
Marked to be transferred to RIV
Yes
Organization unit
School of Business Administration in Karvina
ISBN
978-3-032-11455-6
Keywords in English
LLMs; Process mining; Business process management; AI
Tags
International impact, Reviewed
Changed: 19/10/2026 23:21, doc. RNDr. Ing. Roman Šperka, Ph.D.
Abstract
In the original language
Large language models (LLMs) are a type of deep learning model characterized by an exceptionally high number of parameters. Their significant progress across a wide array of tasks has enabled them to become valuable and versatile tools for a diverse range of applications. Their capabilities present promising opportunities for business process management, although these potential benefits have yet to be thoroughly explored. In this research, we explore the use of LLMs to enhance various aspects of business process management (BPM). The primary focus is on process mining as a subset of BPM. To answer research questions “How are LLMs being integrated with process mining?” and “What are the challenges of integrating LLMs with process mining” we conducted a literature review focused on positioning of LLMs in process mining. In our research we present areas of integration of LLMs in process mining, together with limitations and challenges, and future directions.