XABPs: Towards eXplainable Autonomous Business Processes
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908473504038912 |
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| author | Fettke, Peter Fournier, Fabiana Limonad, Lior Metzger, Andreas Rinderle-Ma, Stefanie Weber, Barbara |
| author_facet | Fettke, Peter Fournier, Fabiana Limonad, Lior Metzger, Andreas Rinderle-Ma, Stefanie Weber, Barbara |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_23269 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | XABPs: Towards eXplainable Autonomous Business Processes Fettke, Peter Fournier, Fabiana Limonad, Lior Metzger, Andreas Rinderle-Ma, Stefanie Weber, Barbara Software Engineering Artificial Intelligence Multiagent Systems 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. |
| title | XABPs: Towards eXplainable Autonomous Business Processes |
| topic | Software Engineering Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2507.23269 |