Many AI pilots fail for reasons that have nothing to do with the model. The gaps are usually in data quality, integration, ownership, and security.
What production needs
Production AI needs a stable use case, a reliable data foundation, clear controls, monitoring, and a plan for what happens when the system is uncertain or wrong.
- Use-case clarity.
- Data and integration readiness.
- Evaluation and fallback behaviour.
The practical approach
The right question is not whether AI can do the task in a demo. It is whether the organisation can operate it safely and improve it over time.