亚马逊内部工程师在员工会议上揭露，公司在导入AI技术时出现多起严重的成本超支事件。其中最突出的案例是使用Anthropic的Claude Sonnet模型进行电商网站作者资料比对，花费高达180万美元，超出预算860%，且耗时五个月才被发现。此外还有约54.1万美元的财务稽核工具开发超支，以及13.4万美元的物流配送AI部署意外支出。资深工程师指出，这些并非个别事件，而是反映了AI部署中缺乏有效支出管控的系统性问题。
亚马逊工程师表示，传统程式设计中「微不足道的廉价」编码错误，在AI模型部署中却可能造成「灾难性的昂贵」后果。公司正在开发自动化的成本防护机制，以防止未来再度发生类似的失控支出。亚马逊官方回应称，这些只是少数团队在学习过程中的个别案例，并不代表公司整体AI运用的常态，并强调公司正持续改进AI的使用效率。（关键数字：300,000, 180）
在更宏观的背景下，亚马逊今年预计资本支出将达到2000亿至2200亿美元，其中绝大部分投入AI与资料中心基础设施，同时正进行大规模裁员以控制成本。整个产业也面临AI部署成本上升的挑战，主要AI供应商已从固定订阅制转向按代币（token）计费模式。亚马逊此前还因员工在内部开发平台上进行「代币灌水」竞赛而被迫关闭相关排行榜，凸显了AI成本管理的复杂性。
Amazon engineers have disclosed multiple instances of severe cost overruns stemming from AI deployments lacking adequate spending controls. The most notable case involved spending $1.8 million using Anthropic's Claude Sonnet model to match author details with ecommerce listings—an 860 percent budget overrun that went undetected for five months. Additional incidents included $541,000 in unexpected costs for financial auditing tools and $134,000 in accidental spending on logistics AI, with the latter taking over two weeks to discover.
Senior engineers warned colleagues that coding mistakes considered trivially cheap in traditional systems were proving catastrophically expensive when teams deployed AI models. The company is now developing automated guardrails to prevent future uncontrolled spending. Amazon responded that these were small, isolated examples of teams learning from one another and did not reflect how AI is broadly used across the company, which employs roughly 300,000 corporate staff and generates about $180 billion in quarterly revenue.
The incidents occur against a backdrop of Amazon's massive AI investment push, with expected capital expenditure of $200–220 billion this year, predominantly directed at AI and data center infrastructure, even as the company undertakes sweeping layoffs to manage costs. The broader industry is also contending with rising AI deployment expenses as providers like Anthropic and OpenAI shift from flat subscriptions to token-based billing. Amazon previously had to shut down an internal leaderboard ranking employees' AI usage after it incentivized token inflation, underscoring the persistent challenge of governing AI costs at scale. (Key numbers: 2000, 2200)