From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining

2026-09-07

AI Summary

本文提出了一种从事件日志到受控行动的过程挖掘方法，旨在将异构操作事件数据转换为可管理的行动，通过结合多种成熟技术实现这一目标。

Abstract

Process mining has long turned event logs into process knowledge: discovered models, conformance evidence, bottleneck diagnoses, and runtime predictions. Agentic AI changes the target. Process-aware agents will not only ask what happened. They will ask whether a proposed action should be taken, given the available evidence, privacy budget, organizational authority, and downstream risk. This BlueSky paper proposes event-to-action process mining: a process-mining agenda for transforming heterogeneous operational event data into governed action. The goal is not another dashboard, a generic enterprise simulator, or a language interface over logs. We argue that the community needs four mineable artifacts: event-object representations, action evidence packages, governance contracts, and benchmarks where act, defer, ask, and refuse are all valid outputs. This agenda is timely because agentic business process management (BPM), LLM-assisted process mining, object-centric event standards, causal process monitoring, and privacy-preserving learning are maturing separately. Bringing them together defines a data-mining target inside process mining: mining logged organizational behavior for accountable action, not only retrospective insight.

Problem

• Agentic AI
• Process Mining
• Event Logs
• Governed Action
• Operational Event Data

Innovation

• agentic process mining
• event-object representations
• action evidence packages
• governance contracts