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Apollo Chief Economist: The profit margins of the seven tech giants are rising, while the rest of the S&P companies are stagnant

The chief economist of the American asset management firm Apollo, Torsten Sløk, released five charts, believing that AI has not yet brought significant financial returns to large American companies outside of the tech giants. The per capita revenue and profit margins of the seven tech giants continue to rise; excluding them, the 493 companies in the S&P have seen these two metrics remain basically stagnant, and the data on total factor productivity in the U.S. has not shown significant signs of AI-driven growth.Apollo cited data from the corporate payment platform Ramp, stating that among its clients, the top 10% of companies by spending contributed 99.5% of the model hosting and inference costs. Among the top 1% of companies with the highest AI spending, about 80% have venture capital backgrounds; for companies at the median spending level, this ratio is only 13%. A large amount of AI computing power consumption is concentrated in a few companies, many of which rely on venture capital support.Previous statistics from Apollo indicated that during the second quarter earnings season of 2026, 69% of S&P 500 companies had disclosed that they were actually using AI, but only 2% reported metrics for ongoing tracking of effectiveness. Another NBER study updated in October this year surveyed nearly 9,000 corporate executives from seven countries, with respondents estimating that over the past three years, AI has only improved the annual growth rate of labor productivity in companies by about 0.2 percentage points.

1% of customer contributions come from Anthropic, while corporate Token spending has nearly stagnated

According to Ramp's tracking of payment data from over 70,000 U.S. companies, approximately 80% of Anthropic and OpenAI's enterprise revenue comes from the top 1% of clients. In August and September, enterprise Token spending saw nearly zero growth for two consecutive months; although it reached a historical high at the beginning of October, it was only 1.5% higher than the peak in August.According to Ornn data, the actual Token price index for Anthropic fell from over $1.70 in mid-September to $0.83, a decline of more than 50%, while OpenAI's corresponding index was $0.45. According to YipitData, the top 1% of Anthropic's clients contributed 46% of revenue in August, up from 25% a year ago. Ramp data shows that the paid adoption rate for enterprise AI in September only increased by 0.62 percentage points to 55.9%. Ramp's chief economist Ara Kharazian believes that growth is shifting from expanding the paid user base to enhancing the depth of use among existing users.Goldman Sachs warns that the growth rate of Token demand must exceed the decline in prices to support sustained investment in computing power. Apollo's chief economist Torsten Slok pointed out that companies are highly sensitive to computing power prices, and price reductions may not necessarily lead to sufficient new demand. Goldman Sachs data also shows that the realized return on invested capital for Amazon, Alphabet, Meta, Microsoft, and Oracle has dropped from 40% to 25%, the lowest since 2016.

first_img The Ramp AI report shows that the adoption rate of Anthropic has surpassed that of OpenAI, with top companies' employees averaging an AI monthly expenditure of $7,449

The economic laboratory of the fintech company Ramp has released a new version of the Ramp AI Adoption Index report. Based on spending data analysis from over 70,000 U.S. enterprise customers, the adoption rate of enterprise-level AI for Anthropic increased by 2.5 percentage points to 41%, officially surpassing OpenAI, which slightly decreased to 39.5%, establishing a leading position in the field of commercial applications.The report focuses on analyzing the spending trends of top enterprises that "deeply adopt AI." Data shows that the top 1% of enterprises spend as much as $7,449 per employee per month on AI, with this figure still achieving a 14.1% increase last month; in contrast, the top 10% of enterprises have an average monthly spending of $611 per employee, while the median enterprise spends only $11.38 (approximately equal to the cost of a single basic subscription).Additionally, the research points out that enterprises that deeply apply AI do not experience "vendor lock-in" and generally adopt multiple cutting-edge large models, open-source platforms, and vertical AI solutions simultaneously. Although enterprises are beginning to experiment with more cost-effective models (such as DeepSeek) in the face of cost pressures, overall AI spending remains on an upward trend.

Enterprise-level AI payment platform Ramp completes $750 million financing at a valuation of $44 billion, led by ICONIQ and others

According to PR Newswire, the enterprise-level AI payment and financial management platform Ramp announced the completion of a new round of financing totaling $750 million, with a post-money valuation of $44 billion.This round of financing was led by ICONIQ, GIC, and the Ontario Teachers' Pension Plan, with participation from institutions such as Goldman Sachs Alternatives, D.E. Shaw, Morgan Stanley Investment Management, Generation Investment Management, and Insight Partners.Ramp stated that the company is expanding its business into the AI cost management field, launching the AI Token spending management tool to help businesses monitor and control expenses related to large models and AI services. In recent months, Ramp has completed acquisitions of the UK and European payment platform Billhop and the business travel platform Juno, and has also deepened its long-term collaboration with Visa to promote AI agents to autonomously execute corporate payments within a real-time risk control framework.Ramp revealed that its internal AI tools have achieved a 99.5% employee adoption rate, with the internally developed platform Inspect currently generating over two-thirds of the company's code. The company plans to use this round of financing to further expand its product layout and accelerate its expansion into the UK and European markets.
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