Every operational function now lives downstream of instruments that never sleep. Monitoring agents, screening engines, quality sensors, planning systems, and lately AI agents generating observations of their own. The volume is not the scandal. The scandal is the routing: everything arrives with equal urgency, addressed to whoever happens to be on shift.
Sanctions screening is the honest extreme, with industry analyses consistently putting false positive rates above 95%. But the same shape runs through control monitoring, demand alerts and infrastructure paging. When one hundred interruptions carry five real risks, the human learns, rationally, to stop being interrupted. The alert that mattered is dismissed in the same batch as the forty that did not.
The discipline with an unfashionable name
The remedy has existed since long before AI: management by exception. Watch everything; escalate only what genuinely requires judgement; handle the rest silently or automatically. It fell out of fashion because the tooling could not honour it. Thresholds were static, context was absent, and every vendor's definition of "exception" was "anything we noticed".
Done honestly, the discipline makes three demands that most alerting systems fail:
- One condition, one alert. A situation is a single decision, not a feed. If the same root cause pages five people through four tools, the system has multiplied noise, not vigilance.
- An exception is a prediction, not a threshold breach. "Inventory below X" fires late and often. "This item will breach its service level in three weeks unless intervened" fires once, early, with odds attached.
- Every alert carries its decision. Who owns it, what the options are, what happens if nobody acts. An alert without an owner and a consequence is a notification, and notifications are where attention goes to die.
The metric that matters is not how many events were detected. It is how few interruptions were wasted.
Why the agentic era makes this urgent
The industry is currently anxious about agent sprawl, and the anxiety is justified: surveys through 2026 keep finding AI deployment far ahead of governance. An IDC InfoBrief commissioned by Kinaxis put the supply chain gap at 88% deployed versus 12% with governance fully embedded. Hundreds of agents observing, recommending and acting will multiply the event stream by orders of magnitude.
The instinctive response is to build a governance layer that watches the agents. There is an older and simpler answer. Put what the agents produce through the same exception discipline as everything else. An agent can flag whatever it likes; only the few items that genuinely need human judgement ever reach a person, and each one arrives with the odds, a named owner and the options. That changes the question. Instead of asking how much we dare let the machines do, you ask which interruptions have earned a person's time. And autonomy stops being a leap of faith. A task is handed fully to the machine only once the record shows that human review of it was changing nothing; the machine takes over only what it has already proven it can do alone.
Watch everything. Interrupt only for judgement. Everything else is either automation or noise.
This is the discipline Prophesee's Pulse engine is built around. Millions of events in, a handful of owned, explained decisions out. See your own event stream through it. Start here.