The Governance Costs Missing From Enterprise Agentic AI ROI Models
One of the most interesting uses of agentic AI is going beyond a predefined path: filling gaps in the specification, finding a way, and acting on it. On paper, the return is obvious. Work that needed a human to find the way can be attempted at machine speed.
The business case for an agent that can find its own way is usually written before the control system is. Capability goes in the numerator. Governance, identity, purpose limits, approvals, evaluation, and the work of writing down what the human already knew go in a footnote called “phase two.”
That is not an accounting error at the margin. It is a comparison between two different products.
Bounded agents on a path you already drew—filters, extraction, a choice among predefined consequential outputs—do not create this path-finding problem. Replacing the human professional can still drop tacit boundaries, but that is a different problem. This...
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