The hardest part of an enterprise AI program is not the model. It is the operating model around it: who owns evaluation, how the system gets retrained, and what the rollback path looks like at 2am.
We treat AI features as production software with a measurement obligation. Before a model goes live, an evaluation harness goes live first. Before the harness goes live, an owner is named.
This is the playbook we use, distilled from twelve enterprise AI deployments in operations, healthcare, and financial services.