{"id":751821,"date":"2026-11-06T19:00:58","date_gmt":"2026-11-06T16:00:58","guid":{"rendered":"https:\/\/buradabiliyorum.com\/en\/ramp-data-shows-ai-spending-stalling-just-as-anthropic-nears-its-ipo\/"},"modified":"2026-11-06T19:00:58","modified_gmt":"2026-11-06T16:00:58","slug":"ramp-data-shows-ai-spending-stalling-just-as-anthropic-nears-its-ipo","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/ramp-data-shows-ai-spending-stalling-just-as-anthropic-nears-its-ipo\/","title":{"rendered":"Ramp data shows AI spending stalling just as Anthropic nears its IPO"},"content":{"rendered":"
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Companies are using more AI than ever, but they\u2019re not spending more on it. <\/p>\n

A new report from Ramp<\/a> shows AI spending flatlined over late summer even as token volumes rose, a sign that price competition and savvier customers may be capp<\/a>ing revenue for OpenAI and Anthropic. According to Ramp\u2019s data, token spend only grew 1.5% across August and September. To compare, in July, it grew 42% from the previous month.<\/p>\n

As Anthropic gears up for its IPO, the data suggests investors might be wrong to assume AI companies will keep growing at breakneck speed.<\/p>\n

\u201cAlmost the entire spend on AI is from venture-backed, high-growth tech companies,\u201d Ramp\u2019s lead economist Ara Kharazian told TechCrunch. \u201cThat\u2019s fine as long as AI spend continues to rise, but if it starts to slow down because of something in the market or some other factor, they will all start to slow down simultaneously, and that could lead to other cascading effects.\u201d<\/p>\n

Kharazian said he\u2019s already seeing evidence that the top 1% of firms \u2014 the most \u201cAI-pilled\u201d \u2014 have stuttered slightly in their spend in August and September, coming up just below the $10,000 per-employee they were hitting at their summer peaks. A slowdown among that cohort is \u201csufficient to slow down revenue entirely, despite the fact that we\u2019re seeing rising volumes,\u201d he said.\u00a0<\/p>\n

Ramp data shows growth in spending among media<\/a>n and top 10%, but it\u2019s not enough to make up the difference. Median firms spend $12-$15 per employee per month, and the top 10% spend $600-$1,000.\u00a0<\/p>\n

\u201cIf you look at the use cases today, it\u2019s not necessarily clear they will get up to that $10,000 per employee per month mark that the 1% is at,\u201d Khazarian said. While there\u2019s plenty of demand for AI coding agents in industries like software and finance, \u201cit\u2019s not necessarily true that a doctor\u2019s office or a car dealership will need to spend that much on AI.\u201d<\/p>\n

\u201cThe era of hypergrowth may be over, and now that we know there may not be as much juice to squeeze out of the top 1%,\u201d he continued.<\/p>\n

October data did see a re-acceleration, with token spend up 8.9% from September 23 to October 23, but Khazarian said the headwinds on spend growth are strong.<\/p>\n

Khazarian (who has published a series<\/a> of blogs called \u201cCracks in the AI Thesis<\/a>\u201d) said the slowdown isn\u2019t due to a demand problem. Again, AI volumes are up. Instead he points to the competitive nature of the marketplace.\u00a0<\/p>\n

\u201cOpenAI and Anthropic price cuts have\u2026just made it cheaper to use AI,\u201d he said. In September, OpenAI cut API prices<\/a> in half for GPT-6 Sol and GPT-6 Luna. Answering the price war, Anthropic has also made significant reductions to pricing for Fable 5.1 and Opus 5.5 \u2014 a decision that the company said in a recent filing slashed revenue growth by about $600 million. Both companies have also been offering enterprise discounts that are intended to lock-in spend, but in reality are hitting their revenue targets.<\/p>\n

Khazarian said this dynamic means it has very much become a buyer\u2019s market.\u00a0<\/p>\n

Subsidizing use of expensive technology<\/a> in order to lock in customers has always been a part of the Big Tech playbook. Just recall how cheap it used to be to take an Uber or Lyft ride, and now that there are few other ride-hail players, the cost of going from A to B has risen significantly. Khazarian says those dynamics don\u2019t work in the AI world because there\u2019s just too much competition.\u00a0<\/p>\n

\u201cMeta and Nvidia are also introducing enterprise offerings with pretty cheap models or open source models,\u201d Khazarian said. He also pointed to the range of other open model companies from China and the United States, as well as a new company called Jev \u2014\u00a0 a lightweight tool for choosing between a few predetermined outputs \u2014\u00a0 that is increasingly among the top performers on Ramp.\u00a0<\/p>\n

\u201cFor a lot of AI use cases, you just need a simple Yes\/No,\u201d Khazarian said. \u201cSo you take your already cheap models, you shift them over to Jev, and now your already cheap stuff gets even cheaper.\u201d<\/p>\n

The ability to complete workloads at a much cheaper cost is another factor driving the spending slowdown. That\u2019s partly due to the discounts from AI companies, but also because companies are just getting better at being thrifty.<\/p>\n

\u201cAs you get really advanced in using AI, you get better at figuring out how to control it,\u201d Khazarian said. \u201cYou\u2019re more likely to use defaults that prevent usage of very expensive models for long-running tasks. You\u2019re more likely to impose some budgets on employees. You\u2019re more likely to offload some of the spend from standard and light models to even cheaper light models via routers.\u201d<\/p>\n

Notion co-founder Akshay Kothari recently posted internal data that matched Ramp\u2019s insights. As he succinctly put it: \u201ctokens go brr. Costs go ahhh.\u201d<\/p>\n

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\u201cA <\/strong>lot of the assumptions that we had about the trajectory of AI spend are starting to break down,\u201d Khazarian said. \u201cYou can use more AI, but use it for less. That\u2019s great for the customers\u2026but it\u2019s not necessarily great for the model companies. And it does introduce new questions around their revenue trajectories.\u201d<\/p>\n

Bloomberg reported Friday that Anthropic\u2019s potential valuation<\/a> sank from the $2 trillion estimated in early October to just $1.2 to $1.3 trillion. The company is also reportedly expected to receive a high \u201cjunk\u201d rating from credit agencies. OpenAI also lowered its proposed <\/a>valuation to $1.25 trillion from $1.4 trillion and slashed its latest fundraising goals by about $10 billion.\u00a0<\/p>\n

Khazarian says Ramp\u2019s dataset likely informs many investor concerns. There is, however, one potential brightside for spending trajectories, albeit a speculative one.\u00a0<\/p>\n

Much of the thesis for hypergrowth spending is that AI will undoubtedly introduce new use cases that will accelerate things. AI coding emerged just a year and a half ago as the most commercially viable product that has led Anthropic and OpenAI to becoming trillion-dollar companies. The hope among investors is that there will be another revolution that will drive further spend.\u00a0<\/p>\n

Some think personal agents will be the next coding agents. OpenAI, SpaceXAI, and Meta have all released their own personal agents, alongside startups like Instinct. Khazarian is skeptical, though, that personal agents, which are \u201cnot as economically productive as coding,\u201d will provide the boost the industry needs for nonstop growth.<\/p>\n

\u201cThe projection is that there will be new products being introduced that will drive further growth,\u201d Khazarian said. \u201cBut based on what we can observe today and the products available and what is commercially advanced, AI spend has started to slow down.\u201d<\/p>\n<\/div>\n

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Companies are using more AI than ever, but they\u2019re not spending more on it. A new report from Ramp shows AI spending flatlined over late summer even as token volumes rose, a sign that price competition and savvier customers may be capping revenue for OpenAI and Anthropic. According to Ramp\u2019s data, token spend only grew…<\/p>\n","protected":false},"author":1,"featured_media":751822,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/techcrunch.com\/wp-content\/uploads\/2026\/11\/ara-stripe-5.png?resize=1200,779","fifu_image_alt":"","footnotes":""},"categories":[18],"tags":[77337,75885,152300,164029,141199,153970],"class_list":["post-751821","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-ai","tag-enterprise","tag-anthropic","tag-enterprise-ai-spend","tag-openai","tag-ramp"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/751821","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=751821"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/751821\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/751822"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=751821"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=751821"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=751821"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}