AI earns its keep in operations when it removes a repetitive cognitive task from a human who is already overloaded. It fails when it's bolted onto a workflow purely so the product page can claim it.
The workflows where AI compounds value share a pattern: high volume, structured-enough inputs, a clear definition of a good outcome, and a human who can course-correct when the model is wrong. Ticket triage, document extraction, anomaly detection in operational data, first-draft report generation — these all fit the pattern. Open-ended "AI assistants" bolted onto dashboards rarely do.
Our rule of thumb is simple. If we can't describe, in one sentence, which human task the model is removing and how we'll measure the time saved, we don't ship the feature. AI in operations is a productivity tool, not a marketing surface.