When companies give employees AI token budgets and track usage on dashboards, it incentivizes ROI-negative behavior. Employees feel compelled to spend their entire allocation to appear productive, a classic example of Goodhart's Law where the metric (usage) undermines the goal (productivity).

By ranking engineers on AI token consumption, Meta is experiencing Goodhart's Law: "When a measure becomes a target, it ceases to be a good measure." Employees reportedly build bots to needlessly burn tokens for status, demonstrating how gamifying a proxy metric can backfire and disconnect from actual business impact.

When a useful metric like "average handling time" becomes a performance target, employees game the system. Reps may hang up on customers to meet quotas, destroying the metric's ability to reflect actual customer satisfaction.

When companies measure AI adoption by counting tokens used, it creates a perverse incentive. Employees and their teams create agents to perform pointless tasks simply to boost their metrics, leading to fake productivity and problematic artifacts.

According to Goodhart's Law, when a measure becomes a target, it ceases to be a good measure. If you incentivize employees on AI-driven metrics like 'emails sent,' they will optimize for the number, not quality, corrupting the data and giving false signals of productivity.

Setting rigid targets incentivizes employees to present favorable numbers, even subconsciously. This "performance theater" discourages them from investigating negative results, which are often the source of valuable learning. The muscle for detective work atrophies, and real problems remain hidden beneath good-looking metrics.

Charles Goodhart's Law states that when a metric becomes a target, its value as an indicator is destroyed because people will manipulate it. For example, support teams might merge tickets to artificially lower resolution times, hitting their target without actually improving service.

Alan Chang argues that incentivizing metrics can have negative second-order effects. For example, a recruiter bonused on 'hires per month' may be motivated to convince hiring managers to lower the talent bar just to hit their target, which is detrimental to the company's long-term goals.

When complex situations are reduced to a single metric, strategy shifts from achieving the original goal to maximizing the metric itself. During the Vietnam War, using "body counts" as a proxy for success led to military decisions designed to increase casualties, not to win the war.