Most AI pilots prove that a model can work. Production delivery must also prove that the data, workflow, controls, user experience, monitoring and operating ownership work together.

Define operational acceptance

Set business, model, safety, latency, cost and user criteria before experimentation begins. A technically accurate model may still be unsuitable for the workflow.

Engineer the surrounding system

Plan data pipelines, feature or knowledge management, APIs, human review, security, observability and failure handling alongside the model.

Release with an operating model

Assign product and model ownership, monitor quality and drift, maintain audit records and establish a controlled process for changes and retraining.

KEY TAKEAWAYS

  • Set acceptance criteria early
  • Build the system around the model
  • Fund ongoing monitoring and ownership