Your AI workflow has ended.
Its controls worked as designed.
Is the operation actually closed?
Organizations can tightly control an individual AI workflow: its access, resources, execution environment and termination.
But those controls govern the workflow. They do not by themselves tell you where the effects of its actions continue.
The OpenAI/Hugging Face incident made that distinction operationally visible.
Agents ran in separate runs and isolated containers. But some could access the same internal infrastructure, allowing information, tools, results and credentials left by one run to become available to another.
The individual runs were separate. The resulting action chain could extend beyond them.
That is the problem even when workflow-level controls work as intended.
The workflow remains a valid governance unit. But its boundary may not contain the full operational effect of its actions.
So what tells your organization that the effects of a workflow have crossed into something its controls no longer govern?
And once they have, what governs what happens next?