Abstract
Low-code development platforms afford fast and easy process automation. Their intuitive drag-and-drop interfaces enable employees without formal programming skills to participate in process au-tomation. However, these so-called citizen developers often struggle to create high-quality automa-tion and face challenges in understanding, maintaining, or reusing existing low-code automation. These issues can severely hamper the effectiveness of citizen developer projects or even prohibit potential citizen developers from partaking. In response, this paper presents an artefact aimed at lowering barriers for citizen developers and assisting them in their process automation. We create de-sign principles and develop an artefact that illustrates the approach using the example of robotic process automation. Building on a large language model with a custom frontend, the proposed artefact lowers barriers to citizen development by automatically interpreting, documenting, and adapting complex low-code automation using natural language. We demonstrate the functionality of our solution and evaluate its value with practitioners.
Recommended Citation
François, Peter A.; Ciftci, Seyyid; Janiesch, Christian; and Plattfaut, Ralf, "Large Language Models for Low-Code Process Automation:
Lowering the Barriers for Citizen Developers" (2025). ACIS 2025 Proceedings. 242.
https://aisel.aisnet.org/acis2025/242