All of China’s AI models put together generate roughly a tenth of the revenue reported by the two leading U.S. AI startups, OpenAI and Anthropic, per the report.
Annual recurring revenues (ARR) of frontier labs and hyperscalers’ AI model businesses have surged this year…,” the report said. “However, the total ARR for all of China’s AI models was still only around $10.7 billion based on the latest available data, which is around 10% of the recently reported levels of OpenAI and Anthropic at this point. For hyperscalers and telecoms, the scale of their cloud service revenues is also quite limited, accounting for around 13% of total revenues.”
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The scale of China’s AI buildout is roughly 15% to 20% of the level of investment seen in the United States, according to the report. AI capital expenditures in China will double this year to 932 billion yuan (about $139 billion). Capex will exceed 1.2 trillion yuan (about $193 billion) in 2027.
“China’s AI firms face similar cash flow problems to their U.S. counterparts, with revenues failing to cover aggressive capex plans by wide margins,” the report said. “Hyperscalers’ cash-generating businesses still depend upon slowing consumption from Chinese households.”
Chinese AI companies are dependent on equity financing and bank loans and have not yet turned to bond financing, unlike their counterparts in the U.S., according to the report. But revenue and profitability metrics for Chinese AI companies still appear “far behind” those of U.S. firms.
“Hence, continued expansion likely depends upon equity market conditions,” the report said. “Even more aggressive state-led investments aligned with China’s industrial policy priorities are likely to remain focused on chips rather than on frontier labs.”
The report follows findings earlier this month from Ramp showing that the top 1% of customers make up 80% of revenue for both OpenAI and Anthropic, a concentration that has remained steady even as more business customers begin paying for generative AI.
“This is a level of concentration risk unseen in any other software category we track,” Ramp Lead Economist Ara Kharazian said in a post on LinkedIn, PYMNTS reported Sept. 4.
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