Ramp Data Shows AI Spending Flatlined as Anthropic Nears Its IPO

Companies are using more AI than ever, but they're 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. As Anthropic gears up for its IPO, the data suggests investors might be wrong to assume AI companies will keep growing at breakneck speed.

The Data Behind the Slowdown

According to Ramp's data, token spend only grew 1.5% across August and September. To compare, in July it grew 42% from the previous month. Ramp's lead economist Ara Kharazian told TechCrunch that almost the entire spend on AI is from venture-backed, high-growth tech companies. That's fine as long as AI spend continues to rise, but if it starts to slow down, they will all start to slow down simultaneously, potentially leading to cascading effects.

Kharazian said he's already seeing evidence that the top 1% of firms — the most "AI-pilled" — 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 "sufficient to slow down revenue entirely, despite the fact that we're seeing rising volumes," he said. Ramp data shows growth in spending among median and top 10% firms, but it's not enough to make up the difference. Median firms spend $12-$15 per employee per month, and the top 10% spend $600-$1,000.

"If you look at the use cases today, it's not necessarily clear they will get up to that $10,000 per employee per month mark that the 1% is at," Kharazian said. While there's plenty of demand for AI coding agents in industries like software and finance, "it's not necessarily true that a doctor's office or a car dealership will need to spend that much on AI."

Price Competition Driving a Buyer's Market

The slowdown isn't due to a demand problem — AI volumes are up. Instead, Kharazian points to the competitive nature of the marketplace. "OpenAI and Anthropic price cuts have just made it cheaper to use AI," he said. In September, OpenAI cut API prices 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 — 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.

Kharazian said this dynamic means it has very much become a buyer's market. He noted that subsidizing use of expensive technology to lock in customers has always been part of the Big Tech playbook — recall how cheap Uber and Lyft rides used to be before competition decreased. However, those dynamics don't work in the AI world because there's just too much competition.

"Meta and Nvidia are also introducing enterprise offerings with pretty cheap models or open source models," Kharazian said. He also pointed to a range of other open model companies from China and the United States, as well as a new company called Jev — a lightweight tool for choosing between a few predetermined outputs — that is increasingly among the top performers on Ramp. "For a lot of AI use cases, you just need a simple Yes/No," Kharazian said. "So you take your already cheap models, you shift them over to Jev, and now your already cheap stuff gets even cheaper."

Companies Getting Better at Controlling AI Costs

The ability to complete workloads at a much cheaper cost is another factor driving the spending slowdown. That's partly due to the discounts from AI companies, but also because companies are just getting better at being thrifty. "As you get really advanced in using AI, you get better at figuring out how to control it," Kharazian said. "You're more likely to use defaults that prevent usage of very expensive models for long-running tasks. You're more likely to impose some budgets on employees. You're more likely to offload some of the spend from standard and light models to even cheaper light models via routers."

Notion co-founder Akshay Kothari recently posted internal data that matched Ramp's insights. As he succinctly put it: "tokens go brrr. costs go ahhh."

"A lot of the assumptions that we had about the trajectory of AI spend are starting to break down," Kharazian said. "You can use more AI, but use it for less. That's great for the customers…but it's not necessarily great for the model companies. And it does introduce new questions around their revenue trajectories."

Impact on Valuations and the IPO Outlook

Bloomberg reported Friday that Anthropic's potential valuation 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 "junk" rating from credit agencies. OpenAI also lowered its proposed valuation to $1.25 trillion from $1.4 trillion and slashed its latest fundraising goals by about $10 billion.

Kharazian says Ramp's dataset likely informs many investor concerns. October data did see a re-acceleration, with token spend up 8.9% from September 23 to October 23, but Kharazian said the headwinds on spend growth are strong. Much of the thesis for hypergrowth spending is that AI will 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. Some think personal agents will be that next wave, but that remains speculative.