Ramp AI Index显示美国企业AI支出10月创新高,环比增速放缓至1.65%
US corporate AI spending hits a new high in October, but growth slows to 1.65 percent
- 1Ramp指数显示10月美国企业AI支出创新高,环比增速放缓至1.65%
- 2支出前1%的企业人均月支出中位数10,200美元、上涨9%,典型企业仅16.32美元
- 3Ramp首席经济学家称1%的企业贡献OpenAI和Anthropic的80%收入
- 4每百万文本token均价上月降21%;客服支出占比从6月0.8%升至10月13.3%
美国企业AI支出创新高但增速明显放缓,预算高度集中于少数风投支持的科技企业,且token单价持续走低。
- 影响:token均价上月下降21%,使用AI的边际成本在降低,试点门槛随之变低;客服等增长场景更倾向便宜快速的模型,低成本起步可行;典型企业人均月支出仅16.32美元,多数同行实际投入仍很小。
- 参考:可考虑按最新token单价重算AI试点预算,优先评估客服或客户成功这类低成本场景;值得用人均AI支出对标Ramp的16.32美元中位数,先定位自身投入水平再决定加码节奏。
- 依据:数据来自Ramp AI Index对8.5万多家美国企业的支付记录,为Ramp官方口径暂无独立验证;Ramp自认样本偏成长型科技公司,AI采用率可能被高估。
US corporate AI spending hit a new high in October 2026, but growth was modest.
The Ramp AI Index, which tracks AI spending among business customers of financial services provider Ramp, showed a 1.65 percent increase month over month.
The heaviest AI users spent somewhat more, according to Ramp. The top one percent of companies by AI spending paid a median of $10,200 per employee per month, up nine percent. A typical company, by contrast, spent just $16.32, a slight increase of less than a dollar from the previous month.
Ramp's data reflects market trends but isn't necessarily representative. The index draws on payment data from more than 85,000 US companies, though free AI tools and usage through personal accounts may be missing from the figures.
According to Ramp, separate metrics on token volume and spending come only from companies using Ramp Token Spend Management and aren't representative of overall AI spending on the platform. The customer base skews growth-oriented, tech-savvy, and larger than US businesses overall, so AI adoption is likely overstated.
OpenAI's spending grows faster than Anthropic's
Business customers' spending on OpenAI grew 2.1 percent month over month, compared with just 0.5 percent for Anthropic. According to Ramp chief economist Ara Kharazian, the structural risks he identified in his earlier analysis persist. One percent of companies drive 80 percent of revenue for OpenAI and Anthropic.
That top tier is mostly venture-backed firms in tech, finance, and technical services. Outside those sectors, AI adoption is barely spreading.
Prices are falling at the same time. The average price per million processed text tokens dropped 21 percent last month, according to Ramp. Usage volume is growing faster than spending, so AI keeps getting cheaper, driven by competitive pressure between OpenAI and Anthropic along with open-weight models from China.
Source: Ramp Rate
SpacexSI also grew strongly at 2.2 percent, making it the fastest-growing software company in Ramp's entire dataset. That likely says more about bias in Ramp's data than about any big win for Grok. The company's models aren't particularly noteworthy, and the growth is probably driven by the coding tool Cursor, which belongs to SpacexSI. On Ramp, the company holds a 6.3 percent market share, a figure that most likely doesn't reflect the broader market. Anthropic reached 44.8 percent adoption, up 1.1 percentage points, while OpenAI held steady at 40.6 percent. Overall adoption of AI services rose to 56.8 percent.
Customer support gains ground as a growth driver
Software development teams accounted for 72 percent of all tracked AI spending in October, but their spending has declined from summer highs. Customer support and customer success departments saw the strongest growth, with their share of AI spending climbing from 0.8 percent in June to 13.3 percent in October, possibly driven by AI chatbots in customer service. Leadership teams also spent slightly more.
Source: Ramp Rate
But customer support is nowhere near matching the rapid growth development teams posted earlier this year, Kharazian writes. These use cases also tend to favor cheaper, faster models over the most expensive flagship ones.
For OpenAI and Anthropic, that means new customers may bring lower margins. The share of the most expensive models, which Kharazian identifies as Opus, Fable, Sol, and Astra, still edged up slightly in October, reaching 69.5 percent of total spending.
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来源:The Decoder:AI News · the-decoder.com