标题： 没有PI就没有AI！ 以对象为中心的过程挖掘作为生成式、预测性和处方性人工智能的推动者 显示英文标题

标题： No AI Without PI! Object-Centric Process Mining as the Enabler for Generative, Predictive, and Prescriptive Artificial Intelligence

摘要： 人工智能（AI）的采用影响了我们工作、互动、经商和进行研究的方式。 然而，组织在工业环境中难以成功应用AI，这些环境关注端到端的操作流程。 在此，我们考虑生成式、预测性和指令性AI，并详细说明诊断和改进此类流程的挑战。 我们表明，AI需要使用以对象为中心的过程挖掘（OCPM）来建立基础。 与文本不同，与流程相关的数据是结构化的且组织特定的，流程通常高度动态。 OCPM是连接数据和流程的缺失环节，并支持各种形式的AI。 我们使用“流程智能”（PI）这一术语来指代能够处理各种对象和事件类型的以流程为中心的数据驱动技术，从而在组织环境中实现AI。 本文解释了为什么AI需要PI来改进操作流程，并强调了成功结合OCPM与生成式、预测性和指令性AI的机会。 显示英文摘要

摘要： The uptake of Artificial Intelligence (AI) impacts the way we work, interact, do business, and conduct research. However, organizations struggle to apply AI successfully in industrial settings where the focus is on end-to-end operational processes. Here, we consider generative, predictive, and prescriptive AI and elaborate on the challenges of diagnosing and improving such processes. We show that AI needs to be grounded using Object-Centric Process Mining (OCPM). Process-related data are structured and organization-specific and, unlike text, processes are often highly dynamic. OCPM is the missing link connecting data and processes and enables different forms of AI. We use the term Process Intelligence (PI) to refer to the amalgamation of process-centric data-driven techniques able to deal with a variety of object and event types, enabling AI in an organizational context. This paper explains why AI requires PI to improve operational processes and highlights opportunities for successfully combining OCPM and generative, predictive, and prescriptive AI.