XABPs: Towards eXplainable Autonomous Business Processes
Software Engineering
2025-08-01 v1 Artificial Intelligence
Multiagent Systems
Abstract
Autonomous business processes (ABPs), i.e., self-executing workflows leveraging AI/ML, have the potential to improve operational efficiency, reduce errors, lower costs, improve response times, and free human workers for more strategic and creative work. However, ABPs may raise specific concerns including decreased stakeholder trust, difficulties in debugging, hindered accountability, risk of bias, and issues with regulatory compliance. We argue for eXplainable ABPs (XABPs) to address these concerns by enabling systems to articulate their rationale. The paper outlines a systematic approach to XABPs, characterizing their forms, structuring explainability, and identifying key BPM research challenges towards XABPs.
Cite
@article{arxiv.2507.23269,
title = {XABPs: Towards eXplainable Autonomous Business Processes},
author = {Peter Fettke and Fabiana Fournier and Lior Limonad and Andreas Metzger and Stefanie Rinderle-Ma and Barbara Weber},
journal= {arXiv preprint arXiv:2507.23269},
year = {2025}
}