内容来源：https://www.wired.com/story/data-center-ai-boom-us-economy-jobs/

内容总结：

【科技巨头万亿押注AI，数据中心热潮重塑美国经济版图】

巨额资本正以前所未有的速度涌入人工智能领域。微软、谷歌、Meta和亚马逊四大科技巨头近期公布，2025年资本支出总额将达约2.6万亿元人民币，且预计2026年将继续增长。其中微软上季度投入约2450亿元人民币用于数据中心建设，相当于其营收的45%。哈佛经济学家杰森·福尔曼指出，2025年上半年美国GDP增长几乎全部来自数据中心和软件处理技术的投资。

资本市场：繁荣背后的隐忧
自ChatGPT问世以来，AI相关股票贡献了标普500指数75%的涨幅和80的盈利增长。科技企业最初依靠丰厚的现金流推进AI项目，但随着投入持续加码，部分企业开始寻求新融资渠道。Meta近期通过特殊目的公司(SPV)筹资270亿美元建设数据中心，又通过发行公司债券融资300亿美元。值得注意的是，企业普遍将AI芯片折旧年限设定为6年，若为保持竞争力需提前升级，或将严重侵蚀利润。

能源危机：算力增长遭遇供电瓶颈
单个数据中心可容纳数万张GPU，运行期间产生的巨大热量对冷却系统提出极高要求。美国电网正承受巨大压力，能源分析师扎卡里·克劳斯警告：“许多建成的数据中心可能面临无电可用的窘境。”2025年上半年美国公用事业公司申请近300亿美元费率上调，而去年美国可再生能源新增装机仅为49吉瓦，同期中国达到429吉瓦。OpenAI已致函白宫，警告电力短缺可能动摇美国在AI领域的领先地位。

就业市场：投资转移引发结构性调整
尽管科技企业利润创新高，亚马逊和微软近期仍分别裁员1.4万和1.5万人。ADP数据显示10月美国私营部门仅新增4.2万个岗位，主要集中在教育和医疗领域。制造业上月减少3000个岗位，反映出资本正从传统领域向数据中心集中。《纽约时报》获得的内部文件显示，亚马逊计划通过自动化技术在2027年前减少16万个岗位招聘。当前就业市场疲软的主因并非AI直接替代，而是资本大规模流向数据中心建设导致的投资失衡。

（本篇报道基于Model Behavior时事通讯内容整编）

中文翻译：

涌入人工智能数据中心项目的资本规模令人震惊。上周微软、字母表、Meta和亚马逊公布2025年资本支出总额将达约3700亿美元，并预计2026年这一数字将持续攀升。上季度最大支出方微软在数据中心等领域投入近350亿美元，相当于其营收的45%。

从未有哪项技术能以如此速度吞噬巨额资金。虽然人工智能泡沫的警告日益高涨，但无论最终是否崩盘，这场狂热已在重塑美国经济格局。哈佛经济学家杰森·福尔曼估算，2025年上半年美国GDP增长几乎全部来自数据中心和软件处理技术的投资。

本期我们将聚焦数据中心如何冲击三大关键领域：公开市场、就业与能源。

资本狂欢
美股繁荣主要得益于人工智能。摩根大通迈克尔·坎巴雷斯特指出，自2022年11月ChatGPT问世以来，AI相关股票贡献了标普500指数75%的回报率和80%的盈利增长。当前核心问题是，随着科技企业持续重金投入AI基础设施，这种增长能否持续。

年初科技巨头主要依靠自有资金推进AI项目。财经记者德里克·汤普森指出，美国十大上市公司在2025年初持有创纪录的自由现金流利润率。换言之，其业务盈利能力极强，可动用的数十亿美元资金足以采购英伟达GPU和建设数据中心。

这一趋势在2025年得以延续。例如字母表上周向投资者透露，今年资本支出将高达930亿美元，较此前750亿美元的预估大幅上调。但该公司同期营收同比增长33%。换句话说，硅谷正在增收增支的双轨上并行。这意味着万事大吉吗？

未必如此。首先，科技巨头可能通过会计手段美化财报现实。大部分AI投资流向英伟达——其GPU迭代周期约为两年。但微软和字母表等企业当前预估芯片使用寿命达六年。若为保持竞争力需提前升级（这种可能性很高），最终将侵蚀利润并削弱整体表现。

部分科技公司近期AI投入过大，被迫寻求新融资渠道。典型案例是Meta近期斥资270亿美元在路易斯安那州建设数据中心集群。该项目通过特殊目的实体（SPV）推进，这种日益常见的架构可避免企业将巨额债务计入资产负债表。上周Meta还通过发行公司债券这一传统渠道融资300亿美元。

能源饥渴
单个数据中心可容纳数万张GPU，在AI训练过程中完成数万亿次运算。这种高强度计算产生巨大热量，需持续冷却硬件确保安全运行。随着AI基础设施竞赛白热化，美国电网正承受空前压力。

症结在于美国电网建设速度跟不上数据中心扩张需求。东达利咨询公司能源分析师扎卡里·克劳斯指出："许多建成的数据中心将面临有设备无电力的困境，因为配套能源资源尚未到位。"

供需失衡推高能源价格，数据中心周边地区尤甚。《纽约客》数据显示，2025年上半年美国公用事业公司申请了近300亿美元的费率上调。

美国清洁能源协会统计，去年美国新增可再生能源装机49吉瓦，而中国同期新增429吉瓦。据传中国政府还向字节跳动、阿里巴巴等本土科技巨头提供丰厚能源补贴以降低其运营成本。

OpenAI上周致信白宫警告："美国发电能力对AI发展的制约，正危及该国在人工智能领域的全球领先地位。"

就业迷思
数据中心建设热潮恰逢劳动力市场疲软。ADP数据显示10月美国私营企业仅新增4.2万个岗位，主要集中在教育和医疗领域。然而科技巨头在披露创纪录利润的同时却在持续裁员：亚马逊上周宣布削减1.4万个企业职位，预计后续还有更多裁员；微软则在5月和7月两轮裁员中裁撤约1.5万人。

虽然表面看来AI导致大规模失业，但实际情况更为复杂。有证据表明生成式AI正在取代软件工程等行业的初级岗位。多家企业也积极推动现有岗位的自动化替代——《纽约时报》获取的亚马逊内部文件显示，通过应用机器人技术，该公司预计到2027年可减少在美国招聘16万人。

但至少现阶段，影响就业的主要因素未必是AI技术本身，而是支撑其运行的数据中心。大型企业和投资者年度资本预算有限，当大部分资金投向数据中心建设时，制造业等领域获得的投资就会缩减——ADP数据显示制造业上月减少了3000个岗位。

本文节选自《行为模式》通讯，过往内容可通过此处查阅。

英文来源：

The amount of capital pouring into AI data center projects is staggering. Last week, Microsoft, Alphabet, Meta, and Amazon reported their 2025 capital expenditures would total roughly $370 billion, and they expect that number to keep rising in 2026. The biggest spender last quarter was Microsoft, which put nearly $35 billion into data centers and other investments, equivalent to 45 percent of its revenue.
Rarely, if ever, has a single technology absorbed this much money this quickly. Warnings of an AI bubble are getting louder every day, but whether or not a crash eventually happens, the frenzy is already reshaping the US economy. Harvard economist Jason Furman estimates that investment in data centers and software processing technology accounted for nearly all of US GDP growth in the first half of 2025.
Today, we’re looking at how data centers are impacting three crucial areas: public markets, jobs, and energy.
Cashing Out
The US stock market is booming, mostly thanks to AI. Since ChatGPT launched in November 2022, AI-related stocks have accounted for 75 percent of S&P 500 returns and 80 percent of earnings growth, according to JPMorgan’s Michael Cembalest. The question now is whether that growth will be sustainable as tech firms continue spending heavily on AI infrastructure.
At the start of this year, tech giants were financing their AI projects mostly with cash they had on hand. As financial journalist Derek Thompson pointed out, the ten largest US public companies kicked off 2025 with historically high free cash flow margins. In other words, their businesses were so profitable that they had billions of dollars sitting around to put towards Nvidia GPUs and data center buildouts.
That trend has largely continued through 2025. Alphabet, for example, told investors last week that its capital expenditures this year would be as much as $93 billion, an increase from its previous estimate of $75 billion. But it also reported that revenue was up 33 percent year over year. Put another way, Silicon Valley is both spending more and earning more. That means everything is fine, right?
Not exactly. For one thing, tech giants appear to be using accounting tricks to make their financials look rosier than they may really be in reality. A significant portion of AI investment flows to Nvidia, which releases new versions of its GPUs approximately every two years. But companies like Microsoft and Alphabet are currently estimating that their chips will last six years. If they need to upgrade sooner to stay competitive—a likely possibility—that could wind up eating into their profits and weaken their overall performance.
Some tech companies have spent so much on AI recently that they have been forced to look for new sources of funding. One noteworthy example is Meta, which recently announced a $27 billion deal to develop a cluster of data centers in Louisiana. The project was created through a special purpose vehicle (SPV), an increasingly common organizational structure that allows firms to avoid putting large amounts of debt on their balance sheets. Last week, Meta said it also raised another $30 billion in debt through a more conventional channel: selling corporate bonds.
Parched for Power
A single data center may house tens of thousands of GPUs that can collectively perform trillions of operations in the course of an AI training run. That massive computing power generates intense heat, and the hardware needs to be cooled to keep running safely. As the race to build AI infrastructure accelerates, it’s placing intense pressure on the US energy grid.
Part of the problem is that the US simply isn’t building enough grid capacity to support all of the data centers currently being built. “I think it is very likely we will see a lot of these facilities constructed with computing equipment in place but there won’t be electrons to power these facilities, because the fuel resources aren’t in place,” says Zachary Krause, an energy analyst at East Daley Analytics who has studied the data center industry.
Because supply can’t keep pace with demand, energy prices are rising, especially in communities near data centers. In the first half of 2025, American utilities sought nearly $30 billion in rate increases, according to The New Yorker.
Last year, the US deployed 49 GW of renewable energy infrastructure, according to the American Clean Power Association. China, meanwhile, added 429 GW. The Chinese government is also reportedly offering generous energy subsidies to domestic tech giants like ByteDance and Alibaba to help keep their energy costs down.
In a letter sent to the White House last week, OpenAI warned that “limits on how much electricity the US can generate to power AI development” are threatening the country’s ability to maintain its global lead in artificial intelligence.
Hiring Haitus
The data center boom is coinciding with a softening labor market. Private employers in the US added just 42,000 jobs in October, mostly in education and healthcare, according to the payroll processor ADP. Big tech companies, however, have been shedding workers, even as they report record profits. Amazon announced last week that it would eliminate 14,000 corporate roles and more cuts are expected soon. Microsoft, meanwhile, laid off about 15,000 people during two rounds of cuts in May and July.
While it’s easy to look at these trends and assume that AI is leading to widespread job loss, the story isn’t quite so simple. There’s some evidence that generative AI is eliminating entry-level roles in certain industries, like software engineering. Many companies are also eager to find ways to automate tasks that humans currently do. Amazon, for example, estimated that it could avoid hiring 160,000 people in the US by 2027 by relying on robots, according to internal documents reviewed by The New York Times.
But at least right now, the main factor impacting jobs isn’t necessarily AI itself, but the data centers powering it. Big companies and investors have a limited amount of capital to spend each year, and they’re putting the majority of it toward building data centers. That means less investment is flowing to other sectors like manufacturing, which lost 3,000 jobs last month according to ADP.
This is an edition of the Model Behavior newsletter. Read previous newsletters here.