Agent Behavior Mining: Generative AI Agent Governance in Business Processes
As organizations increasingly deploy generative AI agents to automate business processes, they face a governance dilemma: although these agents can increase operational flexibility, their non-deterministic nature challenges the control and standardization that Business Process Management seeks to enforce. This paper addresses this \emph{invisible autonomy risk} by introducing \emph{Agent Behavior Mining}, a governance capability that enables the application of process mining techniques to render generative AI agent decision-making observable and traceable. We (1) improve the understanding of generative AI agent behavior through an event data model that translates granular agent activities...
| Authors | Hoang Vu, Maximilian Körner, Adrian Rebmann et al. |
|---|---|
| Primary category | cs.AI |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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