Token maxxing is your AI program’s quiet failure mode
AI investment is accelerating across enterprises.
Budgets are increasing, boardrooms are asking hard questions, and the answer they’re getting back is token costs, prompt counts, and copilot deployment numbers.
Those aren't business metrics. They're activity logs.
Most organizations have settled on those numbers because they’re easy to track and show up well in reports. The problem is that those numbers measure the activity, not the results.
They show how much AI is being used, not whether the business is doing better since implementing it.
This is where token maxxing starts. It happens when organizations begin rewarding those who use AI the most, rather than what it actually delivers.
By optimizing for the wrong thing, we’re quietly setting AI programs up to fail.
When metrics become the mission
There’s a simple truth in business: people optimize for what gets measured, and we’re seeing that with AI right now. Understandably, because teams...
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