Companies are spending less on AI, and it could flash warning signs for the frontier labs.

On Wednesday, Ramp released its monthly AI Index, which tracks AI spend for the payment platform's users, revealing that adoption and spending are both on the downswing. Though Anthropic widened its lead over OpenAI in the past month, new adoption growth is decelerating, according to the index.

Now, as we've reported with previous Ramp data, it's important to remember the caveat that this only measures Ramp customers, which tend to be tech-focused companies and startups. However, among this group, AI adoption numbers have started to sputter over multiple metrics, according to the report:

• Overall adoption, while still growing, continues to slow down, with the share of US businesses adopting AI hitting 56.1% in August, less than half a percentage point increase month-over-month.
• Per-employee spend on AI also fell nearly 10% the past month, dropping from $7,976 to $7,205 among the top 1% of AI adopting firms. Ara Kharazian, chief economist at Ramp, noted in his letter that there are multiple factors driving down this spend, including the innocuous explanation that many people take off work during the summer months. "We’ve similarly observed declines in AI spend around November and December," said Kharazian.
• Additionally, AI token spend is declining as the price of AI starts to drop. Ramp's latest index finds that the "effective price per million tokens" has declined 41% to $0.68 as of the release of the report, down from the 2026 peak of $1.15 in March. For context: OpenAI's Astra and Anthropic's Mythos and Fable 5 and 5.1 cost $10 per million input tokens and $50 per million output tokens.
• And as for frontier labs, the usage of their heavyweight models is seemingly lagging. Adoption and spend is largely driven by lower-cost, mid-tier models like Anthropic's Claude Sonnet or OpenAI's GPT-5.6 Terra. High-powered frontier models like Opus, Fable, and Sol, meanwhile, drove 45% of token share, down from a 53% peak in August.

"The models driving volume increases are relatively cheap … We’ve heard from

businesses who are imposing company-wide defaults that reduce usage of frontier models, saying standard models are still highly performant and also more cost effective," Kharazian wrote.

While the explanation for the decreasing costs could be that companies are leaning into open source models, in reality, the adoption of open source and Chinese alternatives is still limited: According to the report, only 6.4% of businesses that spend on AI use these kinds of models.

Our Deeper View

These indicators are bound to shift as companies navigate their appetites for AI. The "build it and they will come" mindset that frontier AI is currently hitting a speed bump. Meanwhile, average token costs have dropped below a dollar per million while the most powerful models on the market cost more than ten times that. With many users increasingly relying on the lower-tier and lower-cost models from OpenAI and Anthropic, the question emerges why these labs continue to push the frontier at such a rapid pace. While the argument can be made that innovation is needed to continue to move the needle on AI's most advanced capabilities, these labs are putting a lot at risk to create models that push the boundaries, especially when you consider the popularity of their more affordable models that work just as effectively for most business use cases. This could be an opportunity for them to pace themselves and unite on the safeguards needed to move forward more safely.