Ramp data shows business AI adoption slowed in August as per-employee spend fell at top firms
AI spending growth at US businesses slowed in August, Ramp data show: 56% of 70,000 customers paid for AI, up 0.4%, while per-employee AI spend at top firms fell nearly 10% to $7,205 as token prices dropped.
It is not the first time Ramp's metrics have shown adoption flattening. Last year the company's AI index recorded little to no growth in adoption between August and October, before growth picked up again as the year finished. August is also a month when much of the industry is on vacation, which may explain the lull.
The stakes are high for the companies building AI infrastructure. The heavy investment by frontier labs and hyperscalers rests on the hope that there is enough revenue to pay it back, and usage has grown steeply as software engineers adopted agentic coding tools. If adoption slows, revenue is likely to slow with it.
Ramp's figures may overstate adoption overall because its client base skews toward technology companies. An ongoing US Census Bureau survey of AI adoption updated on August 23 shows just 22% of businesses reporting that they use AI. Ramp's survey is not necessarily representative of the wider market, but it is one of the few direct spending data sets available and potentially a leading indicator.
Ramp economist Ara Kharazian pointed to other warning signs for companies that depend on token spend. AI spend per employee at the top 1% of firms in his sample fell nearly 10%, to $7,205. That may reflect vacation-period token use, but it also reflects falling token costs: as OpenAI and Anthropic have cut prices, average token costs have declined to $0.68 per million tokens, against a 2026 peak of $1.15 per million in March.
The data suggests the labs have yet to make up for the price cuts with growing volume, and the same incentives are leading many customers to use older, cheaper models such as OpenAI's ChatGPT 5.6-Terra and Anthropic's Sonnet instead of more powerful frontier releases. Employees at frontier labs have said much of the cost of training a model is recouped in the first weeks of its release, a dynamic that slower adoption could threaten.
Open-weight models have been discussed as a threat to the frontier labs, but only 6.4% of businesses that spend on AI used model-serving or inference platforms in August, a share that is growing steadily but not fast enough to drive the dynamics of broader business adoption.
"We are showing that competition between OpenAI and Anthropic is making AI more accessible, and also driving the price down for companies -- and not just driving the price down, but driving spend down at the top 1% of companies that previously the market was expecting to drive much of the growth going forward," Kharazian said.
That helps explain the focus at AI labs on winning over non-technical users for AI co-working tools. For model builders and hyperscalers with a couple hundred billion dollars of chips on order, a sustained slowdown would be a bad sign. "It depends on who you are in the market," Kharazian said. "If your company is using AI, it's great."