mlsanityData to 14 Oct 2026

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

arXiv 2609.07984 ↗First posted 7 Sep 2026cs.AI cs.CEcited by 0

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 21 of its 26 references that are in the map. First posted on arXiv 7 Sep 2026.

Builds on

21 of 26 references.

Closest ancestors · 2

Same direction, newest first

  1. 2026Agentic Business Process Management: A Research Manifesto19 Mar
  2. 2026PMAx: An Agentic Framework for AI-Driven Process Mining16 Mar

Other references · 19

  1. 2019Advances and Open Problems in Federated Learningcited by 3,046
  2. 2020Consistent Estimators for Learning to Defer to an Expertcited by 271
  3. 2019Process Mining for Python (PM4Py): Bridging the Gap Between Process- and Data Sciencecited by 33
  4. 2020Discovering Object-Centric Petri Netscited by 28
  5. 2022When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraintscited by 11
  6. 2023Leveraging Large Language Models (LLMs) for Process Mining (Technical Report)cited by 9
  7. 2024OCEL (Object-Centric Event Log) 2.0 Specificationcited by 7
  8. 2024ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Predictioncited by 7
  9. 2022Causal Process Mining from Relational Databases with Domain Knowledgecited by 6
  10. 2025Domain Adaptation of LLMs for Process Datacited by 6
  11. 2024A Universal Metric of Dataset Similarity for Cross-silo Federated Learningcited by 4
  12. 2025SimBank: from Simulation to Solution in Prescriptive Process Monitoringcited by 4
7 more
  1. 2026Agentic Business Process Management Systemscited by 4
  2. 2024PM4Py.LLM: a Comprehensive Module for Implementing PM on LLMscited by 3
  3. 2024Intelligent Cross-Organizational Process Mining: A Survey and New Perspectivescited by 2
  4. 2025ProCause: Generating Counterfactual Outcomes to Evaluate Prescriptive Process Monitoring Methodscited by 2
  5. 2026Formal Foundations of Agentic Business Process Managementcited by 2
  6. 2024Digital Twins of Business Processes: A Research Manifestocited by 1
  7. 2026DIFF-ERO: A Conformance-Aware Loss for Deep Learning in Process Miningcited by 1

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Agent Behavior Mining: Generative AI Agent Governance in Business Processes
  2. 2026Process Constitutions and Process Stewards: Towards the Next Generation of BPM for Agentic Organizations
  3. 2026Organizational Memory for Agentic Business Process Execution
  4. 2026Canonical Procedural Actions: An Auditable Annotation Protocol for Tool-Use Agent Traces
  5. 2026Building a Process-Modeling Tool using Agentic AI: An Experience Report on PM4Py-UCM
  6. 2025Agentic AI Process Observability: Discovering Behavioral Variability
  7. 2024Re-Thinking Process Mining in the AI-Based Agents Era
  8. 2026From Logs to Agents: Reconstructing High-Level Creative Workflows from Low-Level Raw System Traces