The Automation Cliff Edge: When Partial AI Automation Is Worse Than None
The first time a team automates 70% of a manual process and ships worse outcomes than before, the diagnosis almost always starts in the wrong place. Engineers look at the automated portion: maybe the model accuracy is off, maybe the pipeline has a bug. What they rarely examine is whether the automation itself—by existing—made the remaining 30% of human work structurally impossible to do well.
This is the automation cliff edge. Not a failure of the automated component, but a failure of the seam between automated and manual.
