LLMs for Intelligent Automation - Insights from a Systematic Literature Review
Journal
20th International Conference on Wirtschaftsinformatik (WI)
Type
conference paper
Date Issued
2025-09-15
Author(s)
Research Team
IWI6
Abstract
Intelligent Automation (IA) aims to overcome the limitations of traditional Robotic Process Automation (RPA) by integrating Artificial Intelligence (AI). One AI technology that promises to address many RPA limitations, such as dealing with unstructured data or changes in the workflow, is Large Language Models (LLMs). However, how LLMs can advance IA has not been systematically investigated so far. To address this gap, we conduct a systematic literature review to examine how LLMs can advance IA. Our findings reveal that LLMs are primarily used to process complex inputs, generate automation workflows from natural language, and guide goal-oriented GUI navigation. Furthermore, we identify a crucial research gap in combining these different intelligence features and enabling continuous learning at runtime. Thus, we contribute by highlighting opportunities for how LLMs could drive even greater advancements in IA.
Language
English
Keywords
Large Language Models (LLMs)
Intelligent Process Automation (IPA)
Intelligent Automation (IA)
Cognitive Automation (CA)
Tool Learning
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher place
Münster, Germany
Pages
17
Event Title
20th International Conference on Wirtschaftsinformatik (WI)
Event Location
Münster, Germany
Event Date
15.09.2025
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
open.access
Name
JML_1043.pdf
Size
495.18 KB
Format
Adobe PDF
Checksum (MD5)
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