Why manufacturing AI pilots die – and the decision layer that saves them
By Surya Teja Chayanam, Account Director, YASH Technologies
In manufacturing, we spend a great deal of time asking whether an AI model is accurate enough for production. It is an important question, but often not the question that determines whether a pilot actually scales.
The harder question comes after the model produces an answer.
Who is allowed to act on it?
Consider a recommendation from an AI system: replenish a part, adjust a plan, intervene on a production condition, or escalate an operating anomaly. A technically sound model may generate the recommendation in seconds. But the organization still needs to know whether the system can act automatically, whether a human must approve the action, when that human can override it, and who ultimately owns the outcome.
That is the decision layer.
In our experience with enterprise AI and Industrial IoT deployments, this is where promising pilots can stall. The model...
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