Vision
Vision
The Exception Economy
Most enterprise AI use is still narrow, concentrated in text production, search, and document interpretation. But the pattern of what gets automated first tells you something about what's left behind. As routine work becomes infrastructure, the manual work that remains — the exceptions, the edge cases, the situations nobody wrote a policy for — starts concentrating two things that used to be spread across every role and every afternoon: cost, and organizational learning. They pull against each other in ways we're only beginning to see.
The Exception Economy
Most enterprise AI use is still narrow, concentrated in text production, search, and document interpretation. But the pattern of what gets automated first tells you something about what's left behind. As routine work becomes infrastructure, the manual work that remains — the exceptions, the edge cases, the situations nobody wrote a policy for — starts concentrating two things that used to be spread across every role and every afternoon: cost, and organizational learning. They pull against each other in ways we're only beginning to see.
Signal and Status
What Exceptions Know
When automated systems handle the predictable middle of a distribution, the cases that don't fit become an organization's main channel for learning that conditions have changed. Before the Firestone recall, the tire industry's monitoring system was working exactly as designed, answering the question it had been built to answer. The warranty claims were answering a different question. One nobody had formally asked.
Who Budgets for the Cases That Don't Fit
Commonwealth Bank of Australia cut forty-five call-center jobs after deploying an AI voice system. Within a month it reversed course: call volumes had risen, overtime was being offered, team leaders were being pulled onto calls. The staffing reduction had been modeled against routine volume. What the automated system wouldn't resolve, and what those cases would require, had not been modeled at all.
The Woman Whose Job Is to Understand What the Algorithm Got Wrong
CONTINUE READINGTwo Meanings of Edge
In software testing, an edge case is a rare input at the boundary of a system's designed range. The system has limits; this input found them.
In organizational life, the phrase shifts. Calling something an "edge case" becomes a way of saying this person's situation does not warrant redesigning our process — technical language wrapped around what is, at bottom, a resource-allocation choice.
Automation widens this gap. When routine work gets cheap, exception handling grows relatively expensive. Organizations develop stronger incentives to describe governance choices as engineering facts, labeling situations "unsupported" when the real issue is that accommodation costs more than anyone wants to spend.
In healthcare prior authorization, HHS OIG found that Medicare Advantage organizations overturned 95% of appealed denials for skilled nursing admissions — but only 18% of denials were appealed. Those patients weren't rare inputs. They were people whose needs the system had chosen not to accommodate, in language that made a spending decision sound like a technical boundary.
Further Exception Reading
Past Articles
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The worst incidents I've worked had nothing broken in them. Nothing down, dashboards insisting the system was fine, and ...