用智能体实现流程自主管理，让系统从执行者变为主动优化者。
Agentic Business Process Management Systems
- 基于流程挖掘构建可感知、会推理的智能体架构
- 支持从人工到全自主的全流程治理连续体
- 适合需要动态优化业务流程的企业级系统设计
自90年代以来，业务流程管理（BPM）领域经历了多轮自动化技术演进。部分技术实现单个任务自动化，另一些则聚焦端到端流程编排。生成式与智能体人工智能（AI）的兴起正开启新一轮变革，其关键在于从自动化转向自主性，从设计驱动转向数据驱动，融合流程挖掘技术。本文基于2025年AI for BPM研讨会的主题演讲，提出智能体业务流程管理系统（A-BPMS）的架构愿景：集成自主性、推理与学习能力的新一代平台。该系统能够感知流程状态、识别优化机会并主动干预，以维持和提升性能。文章强调，此类系统需支持从人类主导到完全自主的流程连续体，重新定义流程自动化与治理的边界。
原文摘要 · Abstract (English)
Since the early 90s, the evolution of the Business Process Management (BPM) discipline has been punctuated by successive waves of automation technologies. Some of these technologies enable the automation of individual tasks, while others focus on orchestrating the execution of end-to-end processes. The rise of Generative and Agentic Artificial Intelligence (AI) is opening the way for another such wave. However, this wave is poised to be different because it shifts the focus from automation to autonomy and from design-driven management of business processes to data-driven management, leveraging process mining techniques. This position paper, based on a keynote talk at the 2025 Workshop on AI for BPM, outlines how process mining has laid the foundations on top of which agents can sense process states, reason about improvement opportunities, and act to maintain and optimize performance. The paper proposes an architectural vision for Agentic Business Process Management Systems (A-BPMS): a new class of platforms that integrate autonomy, reasoning, and learning into process management and execution. The paper contends that such systems must support a continuum of processes, spanning from human-driven to fully autonomous, thus redefining the boundaries of process automation and governance.
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