AI Agents 相关度: 9/10

Agentic Business Process Management: A Research Manifesto

Diego Calvanese, Angelo Casciani, Giuseppe De Giacomo, Marlon Dumas, Fabiana Fournier, Timotheus Kampik, Emanuele La Malfa, Lior Limonad, Andrea Marrella, Andreas Metzger, Marco Montali, Daniel Amyot, Peter Fettke, Artem Polyvyanyy, Stefanie Rinderle-Ma, Sebastian Sardiña, Niek Tax, Barbara Weber
arXiv: 2603.18916v1 发布: 2026-03-19 更新: 2026-03-19

AI 摘要

提出了Agentic业务流程管理(APM)的概念框架,旨在使自主代理在组织中执行流程。

主要贡献

  • 定义了APM的核心概念和架构要素
  • 提出了APM代理应支持的四个关键能力:框架自主、可解释性、会话可操作性和自我修改
  • 指出了实现APM所需的BPM、AI和多智能体系统领域的挑战和研究方向

方法论

理论分析和概念框架构建,通过定义核心概念和能力来阐述APM的愿景和研究方向。

原文摘要

This paper presents a manifesto that articulates the conceptual foundations of Agentic Business Process Management (APM), an extension of Business Process Management (BPM) for governing autonomous agents executing processes in organizations. From a management perspective, APM represents a paradigm shift from the traditional process view of the business process, driven by the realization of process awareness and an agent-oriented abstraction, where software and human agents act as primary functional entities that perceive, reason, and act within explicit process frames. This perspective marks a shift from traditional, automation-oriented BPM toward systems in which autonomy is constrained, aligned, and made operational through process awareness. We introduce the core abstractions and architectural elements required to realize APM systems and elaborate on four key capabilities that such APM agents must support: framed autonomy, explainability, conversational actionability, and self-modification. These capabilities jointly ensure that agents' goals are aligned with organizational goals and that agents behave in a framed yet proactive manner in pursuing those goals. We discuss the extent to which the capabilities can be realized and identify research challenges whose resolution requires further advances in BPM, AI, and multi-agent systems. The manifesto thus serves as a roadmap for bridging these communities and for guiding the development of APM systems in practice.

标签

Agentic BPM Business Process Management Autonomous Agents Multi-Agent Systems AI

arXiv 分类

cs.AI