AI spending per employee slipped at top firms in August

Business adoption of AI tools slowed in August, according to spending data from 70,000 companies collected by payments company Ramp. Just 56% of Ramp customers paid for AI products in August, up only 0.4% from the month before — echoing a similar slowdown last year, when Ramp’s AI index showed little to no growth in adoption between August and October before picking up again by year-end.

The scale of the AI buildout means even small slowdowns matter: the enormous investment in AI infrastructure by frontier labs and hyperscalers rests on the expectation that there’s enough revenue to pay it back. Usage has grown steeply so far, particularly as software engineers adopted agentic coding tools, but if that adoption slows, revenue growth is likely to slow too. Ramp’s numbers may overstate overall adoption given its tech-heavy customer base — a U.S. Census Bureau survey updated August 23 found just 22% of businesses report using AI — but Ramp’s data is one of the few direct spending datasets available, and potentially a leading indicator.

August is typically a vacation month across the industry, which may explain some of the slowdown. But Ramp economist Ara Kharazian points to other warning signs. AI spend per employee at the top 1% of AI-using firms in his sample fell nearly 10% to $7,205 — which may partly reflect vacation timing, but also falling token costs: average token prices have declined to $0.68 per million tokens, down from a 2026 peak of $1.15 per million in March, as OpenAI and Anthropic have cut prices. The data suggests the labs haven’t yet made up for those price cuts with growing volume, and many customers are choosing older, cheaper models over newer, more powerful releases — a dynamic that could threaten labs’ ability to recoup training costs, which employees say is mostly recovered in a new model’s first weeks. Only 6.4% of AI-spending businesses used model-serving or inference platforms in August, a share growing steadily but not fast enough to drive broader adoption trends.

“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.

Why it matters

If the companies expected to drive the next wave of AI revenue are instead spending less per employee, model builders and hyperscalers betting hundreds of billions on future demand may need to find that growth somewhere else.