Corporate AI spending plateaus as price cuts swallow revenue growth, Ramp data shows

The numbers tell a different story from the hype

Companies are using more AI than ever, but they are not spending more on it. A new report from Ramp, the corporate spend management platform, shows AI spending flatlined across late summer even as token volumes continued rising — a sign that price competition and savvier customers are capping revenue for OpenAI and Anthropic.

According to Ramp’s data, token spend grew only 1.5% across August and September 2026. For context, in July 2026, it grew 42% from the previous month. The slowdown has direct implications for Anthropic, which is preparing for an initial public offering that investors have already marked down sharply.

“Almost the entire spend on AI is from venture-backed, high-growth tech companies,” Ramp’s lead economist Ara Kharazian told TechCrunch. “That’s 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.”

The top 1% of AI spenders are hitting a ceiling

Kharazian said he is already seeing evidence that the top 1% of firms — the most AI-intensive companies — have stuttered slightly in their spending during August and September, coming up just below the $10,000 per employee per month 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.

Meanwhile, median firms spend $12 to $15 per employee per month on AI, and the top 10% spend $600 to $1,000. But Kharazian is skeptical that broader adoption will fill the gap. “It’s not necessarily clear they will get up to that $10,000 per employee per month mark that the 1% is at,” he said. While there is plenty of demand for AI coding agents in 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.”

“The 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%,” Kharazian continued.

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 remain strong, and the underlying dynamics have not changed.

Why spending is flat despite record usage

The slowdown is not due to a demand problem. AI token volumes continue to climb. Instead, Kharazian points to the intensely competitive nature of the marketplace, where frontier AI companies are slashing prices to capture market share.

“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 the company said in a recent filing slashed revenue growth by about $600 million. Both companies have also been offering enterprise discounts designed to lock in spend, but in reality, those discounts are hitting their own revenue targets.

Customers are getting smarter about optimization

Beyond vendor price cuts, companies are simply getting better at controlling AI costs. “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 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 put it: “tokens go brrr. costs go ahhh.”

The competitive landscape is also expanding. Kharazian noted that Meta and Nvidia are introducing enterprise offerings with cheap or open-source models. A new company called Jev — a lightweight tool for choosing between a few predetermined outputs — is increasingly among the top performers on Ramp’s platform. “For a lot of AI use cases, you just need a simple Yes/No,” Kharazian said, noting that even already cheap models get shifted to even cheaper providers.

Investors are already marking down AI valuations

The spending slowdown comes at a precarious moment for the AI industry’s biggest names. Bloomberg reported that Anthropic’s potential valuation sank from $2 trillion estimated in early October to just $1.2 to $1.3 trillion. The company is 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 of these investor concerns. “A lot of the assumptions that we had about the trajectory of AI spend are starting to break down,” he 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.”

The big question for investors is whether new use cases will emerge to revive growth. AI coding agents emerged a year and a half ago as the defining commercial product of the current cycle, turning Anthropic and OpenAI into trillion-dollar companies. Some analysts and executives believe personal AI agents — now being released by OpenAI, SpaceXAI, and Meta — could be next. But Kharazian is skeptical that personal agents will drive revenue growth at the same scale, since they are “not as economically productive as coding.”