This Amazon story is the most predictable AI failure mode in corporate history: leadership set “use the AI tool” targets, employees optimized the target, and actual productivity got left in a ditch. Goodhart’s Law isn’t a theory here, it’s the operating system.
If your AI adoption metrics reward clicks instead of outcomes, your team will absolutely game them. Not because employees are evil, but because they’re rational in a KPI regime where job safety depends on dashboards, not whether the business got faster, cheaper, or better.
My hot take: corporate AI is entering its “vanity metric bubble” phase. We’re going to see gorgeous internal slides showing rising AI usage while enterprise AI ROI quietly flatlines, and then executives will blame the tools instead of the incentives they designed.
Founders should treat this as a warning shot: measure cycle-time reduction, error reduction, cost per output, win rate, and revenue impact, not prompt count. “Did people use AI?” is trivia. “Did we ship more value per dollar?” is the only scoreboard that matters.
Rating: 9.3/10 for importance, 7.8/10 for shock value. This isn’t surprising, but it’s a brutally useful lesson in KPI gaming, AI adoption metrics, and why most corporate AI programs fail before they ever reach real enterprise AI ROI.
Stay sharp. — Max Signal
