Corporate AI costs are falling, but companies are using the savings to deploy more AI

- US corporate AI spending has fallen since July even as token usage climbed about 50% to a record in late September, according to Ramp’s AI Index.
- The drop is tied mostly to OpenAI and Anthropic competition.
- The figures suggest cheaper AI is expanding how much companies deploy rather than cutting demand, a dynamic that could grow the market while pressuring provider margins and lifting demand for inference, cloud, and chips.
Companies in the United States continue to pay less for AI despite increasing usage levels, according to a recent study released by Ramp AI Index. This information indicates that the AI price wars are not adversely affecting demand. Instead, companies are now finding it easier to deploy AI on a large scale.
If the above trend continues, one can expect that the companies engaged in supplying chips, cloud capacity and inference will receive a boost in terms of financial gain.
Usage up 50%, spending down since July
Ramp economist Ara Kharazian has stated that the amount of money injected by businesses into AI has dropped after hitting a record high in July when the market was wide open for companies like OpenAI and Anthropic to lower their prices.
Usage has shown the opposite trend completely. Through September, usage has increased nearly 50% and hit an all-time high. Anthropic’s token usage was 51% in the final week of the month, and OpenAI’s was 44.5%. Open-source alternatives, according to Ramp, remained under 5%.
Ramp has collected transaction data from 70,000 U.S. firms, but its token data comes from a smaller API-focused sample that prioritizes large purchasers.
According to Kharazian, competition between Anthropic and OpenAI is “making AI more accessible” to more people while driving down the costs for companies.
Why cheaper tokens can mean more AI, not less
Lower prices do not necessarily imply a declining AI industry. Citadel Securities specialist Frank Flight has asserted in his tokenomics evaluation that the degree of adoption is more and more reliant on the affordability and availability of compute, power, and inference capacity.
Data from Ramp itself shows that the price for effective tokens decreased by 41%, to about $0.68 for one million tokens.
Enterprises route work to the cheapest model that fits
Companies are also getting more selective about which models handle each task. The State of Tokenomics survey of 472 companies found 86% were using or evaluating model routers. Router users were four times more likely to show measurable value to CFOs.
Many companies are also beginning to rely less on frontier models. Today, 51% indicate that they heavily depend on them, while only 24 % think they will still belong to that category in a year.

Tighter cost controls, but still more deployment
KPMG’s Q3 AI Pulse found nearly six in ten leaders reporting measurable AI value. Productivity led at 55%, followed by faster decision-making at 49% and stronger financial performance at 37%.
“AI’s value story is getting sharper,” said Todd Lohr, KPMG’s Vice Chair and Head of Client Technology & Innovation.
BCG likewise found that almost half of companies now generate value from AI.
What falling prices could mean for the market
Cheaper AI could bring automation into workflows that were previously too expensive. The OECD’s AI markets study found quality-adjusted language-model prices falling sharply, while noting that agents can consume far more tokens per task.
That means cheaper tokens may lower unit costs without reducing total AI bills. As adoption spreads, companies may simply use much more AI.
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FAQs
Why is corporate AI spending falling?
Ramp economist Ara Kharazian attributes the decline almost entirely to price competition between OpenAI and Anthropic, alongside cheaper and more efficient standard and lite models.
Are companies actually using less AI?
No. Ramp found token usage up roughly 50% since spending peaked in July, reaching a record at the end of September, even as total spending dropped.
Could cheaper AI end up reducing overall spending?
Not necessarily. Gartner forecasts inference costs per agentic workflow rising more than fivefold by 2028, and Citadel Securities notes that lower unit prices can unlock enough additional usage to offset the cuts.
Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

Ibiam Wayas
Ibiam Wayas has covered the crypto news beat since 2019. He studied Computer Science at National Open University of Nigeria. His work has appeared on various crypto news platforms, including Coinfomania, Crypto News Australia, and AltcoinBuzz. Drawing on his background in Computer Science, he now focuses on crypto, robotics, and longevity news.
















