Companies are deploying AI more extensively than ever before, yet their financial commitment to it has stopped climbing. According to a recent Ramp report, AI expenditure remained essentially static through late summer even while token volumes climbed—an indication that intensifying price competition and increasingly cost-conscious buyers may be putting a ceiling on revenue for OpenAI and Anthropic. Ramp's figures show token spending rising a mere 1.5% across August and September, a sharp contrast with July, when it jumped 42% month-over-month. With Anthropic preparing for its IPO, these numbers raise questions about whether investors are mistaken in assuming AI companies will continue expanding at extraordinary rates. "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."

Kharazian noted he is already observing signs that the top 1% of firms—the most enthusiastic AI adopters—have seen their spending dip slightly in August and September, landing just under the $10,000 per-employee level they had reached at their summer peaks. A deceleration within that group is "sufficient to slow down revenue entirely, despite the fact that we're seeing rising volumes," he explained. Ramp's data indicates growth in spending among the median and top 10% of firms, but it isn't enough to close the gap. Median companies spend $12–$15 per employee each month, while 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," Khazarian said. Although demand for AI coding agents is strong in sectors 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."

"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%," he continued. October data did show a re-acceleration, with token spend up 8.9% from September 23 to October 23, but Khazarian cautioned that headwinds against spending growth remain powerful. Khazarian (who has published a series of blogs titled "Cracks in the AI Thesis") emphasized that the slowdown is not driven by weak demand—AI volumes are, after all, rising. Instead, he attributes it 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 halved API prices for GPT-6 Sol and GPT-6 Luna. In response to the price war, Anthropic also made substantial reductions to pricing for Fable 5.1 and Opus 5.5—a move the company said in a recent filing cut revenue growth by roughly $600 million. Both companies have additionally been offering enterprise discounts meant to lock in spending, but which in practice are undercutting their revenue targets. Khazarian said this dynamic means the market has very much become a buyer's market.

Subsidizing the use of expensive technology to lock in customers has always been part of the Big Tech playbook. Recall how inexpensive Uber and Lyft rides once were, and how, now that few other ride-hail players remain, the cost of getting from point A to point B has risen substantially. Khazarian argues those dynamics don't apply in the AI world because there is simply too much competition. "Meta and Nvidia are also introducing enterprise offerings with pretty cheap models or open source models," Khazarian said. He also pointed to the array 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," Khazarian said. "So you take your already cheap models, you shift them over to Jev, and now your already cheap stuff gets even cheaper."

The capacity to complete workloads at far lower cost is another factor driving the spending slowdown. That stems partly from discounts offered by AI companies, but also from companies simply becoming more adept at economizing. "As you get really advanced in using AI, you get better at figuring out how to control it," Khazarian 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 shared internal data that echoed Ramp's findings. As he succinctly put it: "tokens go brr. Costs go ahhh."

"A lot of the assumptions that we had about the trajectory of AI spend are starting to break down," Khazarian 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."

Bloomberg reported Friday that Anthropic's potential valuation dropped 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 likewise lowered its proposed valuation to $1.25 trillion from $1.4 trillion and cut its latest fundraising goals by about $10 billion. Khazarian says Ramp's dataset likely informs many investor concerns.

There is, however, one potential bright spot for spending trajectories—albeit a speculative one. Much of the case for hypergrowth spending rests on the belief that AI will undoubtedly introduce new use cases that accelerate things. AI coding emerged just a year and a half ago as the most commercially viable product, propelling Anthropic and OpenAI to trillion-dollar status. Investors hope another revolution will drive further spending. Some believe 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 "not as economically productive as coding"—will deliver the boost the industry needs for uninterrupted growth. "The projection is that there will be new products being introduced that will drive further growth," Khazarian said. "But based on what we can observe today and the products available and what is commercially advanced, AI spend has started to slow down."