Apply and Commit: Capture the AI Exception Trace

Create a trace-capture routine for AI transport exceptions before root-cause analysis begins. Use it for wrong ETA messages, bad route recommendations, incorrect carrier scoring, yard-vision misses, or unsafe dispatch suggestions. For each AI exception, I will capture [shipment/load ID], [AI workflow], [prompt or rule version], [input/source records], [model output], [confidence or flags], [human action], [timestamp], and [customer/operational impact] before changes are made. In 2 days, check whether the trace fields were added to an incident template or shared with the dispatch/analytics team. A wrong AI-generated ETA update for a shipment that triggered a customer escalation. A route recommendation that caused…

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