Executive Summary
Operational AI should be funded as a service decision, not a model decision.
- Scale services with measurable value, bounded data, clear ownership, and recoverable failure.
- Constrain AI that informs consequential decisions in finance, care, employment, safety, compliance, or regulated workflows.
- Reposition services where review, rework, exceptions, or control cost absorb the expected benefit.
- Pause services with unclear ownership, broad authority, weak recovery, or unresolved process instability.
- Ignore GenAI where rules, integration, workflow automation, or process redesign will solve the problem more reliably.
The immediate risk is not simply inaccurate output. It is AI becoming embedded in enterprise software, connected to internal data and tools, and granted authority before service governance catches up.1,2
Overview
Most enterprises are still asking this AI question: Is the model reliable enough?
That question is too abstract to govern investment. Large language models are not deployed as isolated reasoning engines. They are embedded in services: a …