The blank-check era for enterprise AI is dead. But the CFO's mandate for hard ROI is failing at the API level. Gradient Flow notes finance teams demand measurable returns, yet cannot reconcile what they actually buy.
Look at the telemetry. Holori finds basic FinOps tools log a fraction-of-a-cent automated greeting and a multi-dollar autonomous code review identically: as a single API request. This reporting artifact is a shield. It allows engineering to bury inefficient R&D token burn inside aggregate "production" workflows, masking the true cost of multi-step agentic loops.
When you cannot tie dollars to outcomes, you bleed cash. Digitide reports 2-5x cost inefficiencies for identical use cases. Management sells "value creation," but Virtasant's 2026 data reveals 86% of engineering budget holders do not know which AI tools deliver business benefit.
For FP&A, the operational fix is immediate: stop approving blanket AI infrastructure renewals on historical run rates. Force engineering to implement cost-tagging at the API header level. Shift budget controls from aggregate cloud spend to strict margin-per-AI-feature unit economics. If engineering cannot calculate the token cost of a specific business task, freeze budget expansion.
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