Enterprise spending on AI tools cooled in August, with the top 1% of firms cutting AI spend per employee by nearly 10% to $7,205, according to new data from payments company Ramp, which tracks spending across 70,000 businesses. Overall, 56% of Ramp customers paid for AI products in August, a rise of just 0.4% from July — a pace that contrasts sharply with the steep adoption growth seen earlier in the year, particularly for agentic coding tools.
Ramp’s AI index has shown similar seasonal slowdowns before. Last year, adoption growth nearly flatlined between August and October before picking up again in the final months of the year. But the current data arrives at a delicate moment for the AI industry, where massive infrastructure spending by frontier labs and hyperscalers depends on sustained revenue growth to justify the investment.
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Falling token costs squeeze revenue despite growing usage
Ramp economist Ara Kharazian points to falling token costs as a key factor behind the spending dip. As OpenAI and Anthropic have cut prices, the average cost per million tokens has dropped to $0.68, down from a 2026 peak of $1.15 in March. The price cuts have yet to be fully offset by increased volume, the data suggests.
Many customers are also choosing older, cheaper models like OpenAI’s ChatGPT 5.6-Terra and Anthropic’s Sonnet rather than the latest frontier releases. Employees at frontier labs have noted that much of a model’s training cost is recouped in the first weeks after release — slower adoption of new models could threaten that dynamic.
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“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.
Context and caveats: What the data does and doesn’t show
Ramp’s figures may overstate overall AI adoption because its customer base skews toward technology companies. An ongoing US Census Bureau survey updated on August 23 shows only 22% of businesses report using AI. Still, Ramp’s dataset is one of the few direct spending metrics available and is considered a potential leading indicator for the broader market.
The August timing also matters — much of the industry is on vacation, which may explain the slowdown. But the data also shows that open-weight models have not yet disrupted the market: only 6.4% of AI-spending businesses used model-serving or inference platforms in August, a share that is growing steadily but remains small.
What this means for AI labs and enterprise buyers
For AI labs and hyperscalers with billions of dollars in chip orders, the slowdown is a potential warning sign. If adoption growth continues to decelerate, revenue may not keep pace with infrastructure costs. That pressure helps explain the recent focus at AI labs on winning over non-technical users with AI co-working tools.
For businesses using AI, the trend is more positive. Lower token prices and competitive pressure from OpenAI and Anthropic are making AI more affordable and accessible. “It depends on who you are in the market. If your company is using AI, it’s great,” Kharazian noted.
Whether August marks a seasonal blip or the beginning of a broader slowdown will become clearer in the coming months. Ramp’s data from last year suggests adoption can rebound, but the stakes are higher now, with infrastructure spending at record levels.
Disclaimer: This article is for informational purposes only and does not constitute financial advice. The AI market is volatile and subject to rapid change; readers should conduct their own research before making investment decisions.
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