The demo is not the workflow

The demo is not the workflow. That is my current read on enterprise AI. OpenAI launching a Deployment Company and Anthropic introducing enterprise AI services are easy to frame as "consulting with AI branding." But that reaction also reveals the real issue: model access is no longer the whole problem. The hard part is getting AI into a workflow with: * trusted inputs * a bounded job * a named owner * review points * exception paths * permission boundaries * a maintenance loop If those are missing, a better model may only make the ambiguity more convincing. My question before enterprise AI rollout would be: "Which workflow is clear enough that AI can improve it without creating more review debt?" Not every team needs a giant governance program. But every serious AI use case needs to know what source it trusts, who owns the output, what requires human review, and what happens when the case is not normal. The product is not just the model. It is the model plus the workflow it can reliably change.