“It’s going to be an absolute nightmare(绝对的噩梦),” says an executive at a big American tech company. He is talking about an emerging problem for businesses that use artificial intelligence. AI agents(代理（AI程序）)—bots that can read, interpret and act—use masses of processing power and have started to run up huge bills. As they proliferate(激增，扩散), the problem will grow. Big companies, the executive points out, typically use hundreds of software programs. If each of those offers agents (as they probably will), AI costs could spiral out of control.(如果每个程序都提供代理（很可能会如此），AI成本可能会失控地螺旋上升。)
“这绝对会是一场噩梦，”一家美国大型科技公司的高管表示。他谈的是使用人工智能的企业面临的一个新问题。AI代理——能够阅读、解读并采取行动的机器人——消耗大量处理能力，并已开始产生巨额账单。随着它们激增，问题会进一步恶化。这位高管指出，大公司通常使用数百个软件程序。如果每个软件都提供代理（很可能会如此），AI成本可能会失控。
Budget management is a new worry for AI adopters. Not long ago employees were encouraged to binge on(大量使用（沉迷）) the technology. Burning through vast numbers of tokens(代币（文本处理单位）)—the chunks of text that models process, which are often used as a unit of pricing—became a badge of honour(荣誉徽章（象征）); techies dubbed(被称作，被称为) it “tokenmaxxing”. Companies showed off staff’s AI use on internal leaderboards(排行榜). Meta’s display awarded top users titles like “Token Legend”.
预算管理成为AI采用者的一个新忧虑。不久前，员工还被鼓励大量使用这项技术。消耗大量token——模型处理的文本块，常被用作定价单位——成了一种荣誉徽章；技术人员称之为“tokenmaxxing”。公司在内部排行榜上展示员工的AI使用情况。Meta的展示板授予顶级用户“Token Legend”之类的称号。
Such incentives partly explain the boom in AI spending. So does a change in the way enterprises use the technology. Token-heavy applications, such as reasoning models(推理模型) and agents, are growing more popular. In some cases agents build their own agents(自行创建代理), sending costs higher still. Ramp, a corporate-credit-card provider, analyses its clients’ transaction data to shed light on(揭示，阐明) their AI use. It reckons(估计，认为) their spending has risen 13-fold in the past year. In April Uber said that it had spent its annual AI budget in four months. Other firms have similar problems. One reportedly spent $500m on AI tokens in a month. Sam Altman, the boss of OpenAI, has called mounting(不断增加的) customer costs “a huge issue”.
这类激励措施部分解释了AI支出的激增。企业使用技术的方式发生变化也是原因之一。高token消耗的应用，如推理模型和代理，越来越受欢迎。在某些情况下，代理会自行创建代理，进一步推高成本。企业信用卡提供商Ramp分析其客户的交易数据，以揭示他们的AI使用情况。该公司估计，过去一年客户的支出增长了13倍。今年4月，Uber表示它已在四个月内花光了全年的AI预算。其他公司也有类似问题。据报道，一家公司一个月内在AI token上花费了5亿美元。OpenAI的老板山姆·奥尔特曼称不断攀升的客户成本是“一个大问题”。