Enterprises are unleashing AI agents to streamline workflows, granting them ever‑greater decision‑making power. While this promises efficiency, it also opens a hidden risk: automation can drift from intended goals, operating like an undercover operative no one can see. Without visibility, companies risk costly errors and compliance breaches.
Process mining emerges as a critical countermeasure. By ingesting event logs from enterprise systems, it reconstructs the actual flow of activities, exposing exactly what AI agents are doing in real time. This transparency turns opaque automation into a traceable process, allowing teams to spot deviations and intervene before rogue behavior escalates.
In practice, process mining becomes the “undercover agent” that monitors AI, ensuring alignment with business rules and regulatory standards. Organizations that embed mining into their AI governance can maintain control, improve accountability, and harness the full promise of autonomous automation while keeping unexpected surprises at bay.
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