The top 1% of companies by AI spend now pay a median $10.2K per employee per month for AI, Ramp economist Ara Kharazian writes in the November update of the Ramp AI Index, published on 11 November. The median firm spends $16.32. By our arithmetic, the top group spends about 625 times as much per employee as the median firm.
Kharazian repeats the concentration finding behind those figures: “1% of businesses drive 80% of the revenues to OpenAI and Anthropic”. He writes that this top 1% is “largely made up of VC-backed companies in tech, finance, and technical services”.
Business Pill · Concentration Explained
An evergreen Business Engineer explainer on customer and revenue concentration. It teaches the general idea only and does not discuss Ramp’s data.
The key insight: Ramp’s November AI Index puts the top 1% of companies by AI spend at a median $10.2K per employee per month, about 625 times the median firm’s $16.32 by our arithmetic, and Ramp economist Ara Kharazian writes that 1% of businesses drive 80% of the revenues to OpenAI and Anthropic. Total AI spend rose 1.65% in October while the average price per million tokens fell 21%, according to the letter.
The index tracks how American businesses use AI through spend data from Ramp, according to the letter. AI spending rose to a new peak in October, up 1.65% from September. Spend by the top 1% rose 9% to the $10.2K median. Firms in the top 10% spent $801, roughly flat, and the median firm’s spend rose by $0.93.
Kharazian writes that “The risks I identified in the Cracks series remain”. Besides concentration, he lists sluggish growth outside the top sectors and falling model prices: the average price per million tokens fell 21% over the last month. Our earlier piece covered the October letter’s version of the 80% finding.
AI spend per employee per month in October 2026 by spender group, from the Ramp AI Index November update: the top 1% of firms (median) at $10,200, the top 10% at $801 and the median firm at $16.32. The 625x ratio is our arithmetic.
The Concentration in Numbers
Per employee per month, the top 1% median of $10.2K is about 625 times the median firm’s $16.32 and about 12.7 times the top 10% group’s $801, by our arithmetic. Total spend rose 1.65% in a month in which the average price per million tokens fell 21%, according to the letter.
In October, AI token spend grew 2.1% month over month for OpenAI and 0.5% for Anthropic, Kharazian writes. On adoption, Anthropic rose 1.1 percentage points to 44.8% of Ramp businesses while OpenAI held flat at 40.6%, a lead of 4.2 points by our arithmetic. Overall AI adoption reached 56.8%.
Among Ramp businesses, 6.3% paid SpaceXAI, up 2.2 percentage points from September’s 4.1%, or about 1.5 times in a month by our arithmetic. Kharazian writes: “Expect this two-way race to quickly turn into a 3-way race that puts greater price pressure on OpenAI and Anthropic”. We covered SpaceXAI when it topped Ramp’s fastest-growing list.
Spend Beyond Coding
The letter adds a new dataset: AI spend by department. Engineering teams drove 72% of all classified spend in October, though Kharazian writes that spend has fallen from highs observed earlier this summer. Customer success and support operations drove 13.3% of classified spend, up from 0.8% in June, about 16.6 times the June share by our arithmetic.
Kharazian writes that these use cases are a good candidate for cheaper and faster models. The frontier models’ share of spend rose to 69.5% in October from 67.7%, according to the letter, which names Opus, Fable, Sol and Astra as those models.
The Structural Read
As we read the letter, the two labs’ businessrevenue in Ramp’s data rests on a small, correlated group: Kharazian describes the top 1% as largely VC-backed companies in tech, finance and technical services. Adoption is still widening, to 56.8% of Ramp businesses, but the new adopters and new departments, such as customer support at 13.3% of classified spend, are the use cases he calls a good candidate for cheaper and faster models.
Ara Kharazian, Ramp economist, in the Ramp AI Index November 2026 update
“Expect this two-way race to quickly turn into a 3-way race that puts greater price pressure on OpenAI and Anthropic”
Three Implications
FOR CONCENTRATION The top 1% median of $10.2K per employee per month is about 625 times the median firm and about 12.7 times the top 10%, by our arithmetic.
FOR THE TWO LABS Anthropic’s adoption is 44.8% and OpenAI’s 40.6%, a 4.2-point gap by our arithmetic, while OpenAI’s October token spend grew 2.1% and Anthropic’s 0.5%, according to the letter.
FOR PRICING The average price per million tokens fell 21% in a month and SpaceXAI reached 6.3% of Ramp businesses, up 2.2 points, according to the letter.
The framework says: “The cost of intelligence is collapsing while the cost of deploying intelligence is exploding.”
As we read it, Ramp’s October data shows both halves in one month: the average price per million tokens fell 21% while total AI spend still rose 1.65%, led by the top 1%. The framework predates the letter and does not discuss it.
Share of Ramp businesses paying each provider, from the Ramp AI Index November 2026 update. September values are our arithmetic from the October levels and changes the letter reports.
What Is Not Established
Ramp’s data covers businesses that pay through Ramp; the letter does not give its sample size or say how far the pattern holds outside Ramp’s customer base. The 80% figure describes revenues to the two labs from businesses in Ramp’s data, not either company’s total sales. The September values for adoption are our arithmetic from the changes the letter reports.
Ramp, OpenAI and Anthropic were not contacted for this piece.
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In Ramp’s November index, the top 1% of companies by AI spend pay a median $10.2K per employee per month, about 625 times the median firm, by our arithmetic, and Kharazian writes that 1% of businesses drive 80% of the revenues to OpenAI and Anthropic. Anthropic’s adoption lead over OpenAI is 4.2 points, and SpaceXAI reached 6.3% of Ramp businesses.
A note on sourcing. All Ramp figures and quotations come from Ara Kharazian’s November 2026 Ramp AI Index letter, published by Ramp Economics Lab on 11 November 2026, which we read in full. The ratios, the September adoption values and the point gaps are our arithmetic. Ramp’s figures cover businesses in its own spend data. Ramp, OpenAI and Anthropic were not contacted for this piece.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
