Top U.S. companies spent $7,400 per employee on AI in July, per the Ramp AI Index. Anthropic leads with 43.5% adoption, but its pricier Fable 5 model struggles to gain traction. CFOs shifted expectations sharply.
Alpha Score of 64 reflects moderate overall profile with strong momentum, moderate value, moderate quality, moderate sentiment.
The top 1% of U.S. businesses spent a median of $7,400 per employee on artificial intelligence in July. The top 10% spent roughly $650, and the median company spent $11.95 per employee, according to the Ramp AI Index released Aug. 12. That leaves the heaviest spenders with AI budgets more than 600 times larger, per employee, than a typical business.
Anthropic captures the biggest chunk of that corporate money. Some 43.5% of U.S. businesses paid for its subscriptions or tokens as of July, up 1.1 percentage points from the prior month, Ramp found. OpenAI added just 0.23 percentage points over the same period. xAI notched its fastest growth since July 2025, reaching 4% of businesses.
The spending has a ceiling, even among the biggest adopters. Anthropic released Fable 5, its most capable model, in July at roughly $10 per million tokens: twice the price of OpenAI's GPT-5.6 Sol. One month after launch, Fable 5 made up only 6% of the tokens businesses bought from Anthropic and 11.4% of total dollars spent on Anthropic models, according to Ramp.
OpenAI's cheaper GPT-5.6 Sol captured 25% of OpenAI's tokens and 23% of its spend over the same period. Fable 5 generated about 75% as much total spend as Sol despite being marketed as the superior model.
"With Fable 5, we found a new upper bound for how much businesses are willing to spend on AI," Ara Kharazian, Ramp's lead economist, wrote. To move businesses onto the newest models, he added, the labs "will need to prove performance beyond what even Fable 5 is able to achieve and simultaneously ensure that competitors aren't able to come reasonably close."
Cheaper alternatives are picking up share. Adoption of model-serving platforms that offer open-source and Chinese-developed models kept climbing, reaching 6.1% of AI-adopting businesses, up 0.2 percentage points from the prior month. The shift is slow but steady, even as first-time AI buyers still default to the major American labs.
The outlook among finance chiefs has shifted sharply. The share of CFOs expecting very positive returns from generative AI within one to two years jumped from zero to 39.1% since mid-2025, according to PYMNTS Intelligence. The share expecting the payoff to take three to five years fell from 65.9% to 34.8%.
The bottleneck is internal, not technological. About 71% of senior technology executives at companies with at least $1 billion in annual revenue said organizational readiness, not the AI itself, is the primary factor limiting performance, PYMNTS Intelligence found in its Enterprise AI Benchmark Report. Only 11% blamed the technology.
Earnings data is starting to show some effect, slowly. Only 2% of S&P 500 companies quantified AI effects in second-quarter earnings reports. Of those that did, 11% cited measurable productivity gains in software coding or customer support, according to a Goldman Sachs analysis that PYMNTS reported.
The early returns favor the companies tracking the data. Median earnings rose 17% at companies that quantified AI again, compared with 14% for those that did not. The gap is modest, but it suggests early movers are pulling ahead before most companies have built the reporting discipline to prove the benefit.
Corporate AI is running at two speeds: a small group betting heavily while everyone else buys cautiously.
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