Why AI pilots stall after month three
The exciting first sprint passes. The novelty fades. The metric isn't moving as fast as the demo suggested. Welcome to month three of an AI pilot.
Two reasons dominate: the success metric was vague, and the human review burden was underestimated.
Both are fixable in a single 60-minute meeting if you catch them early.
Pilots that name the metric and reset the review burden up front rarely stall.
Reason 1: vague metric
If the success metric was 'become more efficient,' you don't have a metric. You have a wish. Pilots without a sharp number to hit drift, because no one can say whether they're winning or losing.
Reason 2: human review tax
Every AI workflow needs human review. If the review takes nearly as long as the original work, you have a tie, not a win. Pilots that hit month three without doing this math are usually slower than the manual process they replaced.
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