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Amazon ends internal AI usage leaderboard after staff allegedly inflate token use, as firms like Microsoft and Uber face soaring AI costs and cut or blow through budgets
Amazon Employees Accused Of Inflating AI Token Usage To Meet Targets
The transition to AI does not appear to be as smooth as many had initially expected. Once viewed as a panacea for boosting productivity and efficiency while reducing operational costs, AI is now presenting companies with new challenges as they integrate the technology into their daily workflows.
Amazon employees have allegedly been inflating AI token consumption — a practice colloquially known as “tokenmaxxing” — to meet internal usage targets, according to a Financial Times report.
As a result, Amazon has reportedly shut down its internal leaderboard that tracked employees’ use of AI tools.
Employees told Financial Times that there was significant pressure to use AI tools and meet usage targets. According to the report, some Amazon staff used MeshClaw, an in-house AI agent platform capable of initiating code deployments, triaging emails, and interacting with Slack, to maximise their token usage figures.
This behaviour reportedly increased the company’s computing costs and overall expenditure. Dave Treadwell, Amazon’s senior vice-president, reportedly advised employees not to use AI merely for the sake of using it. In a statement to the publication, Amazon said that “the beta dashboard was not a formal or approved tool and has since been deprecated.”
Rising Cost of AI Adoption
Several major companies, including Microsoft and Uber, that have integrated AI into their workflows are reportedly facing similar challenges as usage costs continue to rise.
Microsoft has reportedly cancelled most of its Claude Code licences after token-related expenses surged beyond expectations.
Meanwhile, Uber is said to have exhausted its entire 2026 AI budget by April. According to reports, the company’s COO admitted that the spending had yet to translate into meaningful consumer-facing features.
In another example, one company reportedly spent $500,000 on AI initiatives without achieving the expected return on investment, highlighting the growing concern among businesses over balancing AI adoption with cost efficiency.
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