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Agentic Business Process Management: A Research Manifesto

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NOW LET US Article – Agentic Business Process Management: A Research Manifesto

Agentic Business Process Management (APM) represents a paradigm shift from traditional automation to systems where autonomous agents perceive, reason, and act within process frames. This manifesto provides a roadmap for integrating AI and BPM to align agent behaviors with organizational goals.

Computer Science > Artificial Intelligence

Title:Agentic Business Process Management: A Research Manifesto

View PDF HTML (experimental)Abstract: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.

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Source: arXiv cs.AI Recent

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