Who is really buying China’s humanoid robots?

China’s humanoid robot makers are generating much of their revenue from selling machines to government-backed training centres — which then collect and sell training data back to the robot makers, raising concerns about actual demand in an industry Beijing is keen to promote.

The widely adopted model, reminiscent of Nvidia’s “circular financing” of AI data centres, has fuelled China’s so-called embodied AI industry. Valuations of start-ups such as AgiBot and Hong Kong-listed UBTech have soared on expectations that humanoids represent the future of AI.

But investors are beginning to question whether government-driven purchases can lead to real commercial demand.

“There is a broad consensus among early-stage investors that humanoid robotics is approaching the peak of the hype cycle,” said a senior investor at a Beijing-based venture capital fund who asked not to be named. “We’re looking for opportunities to sell down some of our holdings to other investors and secure an exit.”

As part of Beijing’s plan to develop China’s humanoid robot industry, it has encouraged local governments to build large-scale training centres, where humans “teach” robots how to perform physical tasks through a remote-controlled process called teleoperation.

This has encouraged the proliferation of robotics start-ups. Nearly 370 have been established in the past two years, and more than 50 of them have listed or are preparing to go public. The most closely watched, Unitree, surged more than 600 per cent after listing on Shanghai’s tech-focused Star Market on Wednesday, giving it a $50bn valuation.

The centres, often co-funded by local governments and robot makers, buy the machines, generate training data and sell the data to the robot makers to improve their technology.

“This model is spreading rapidly because it reduces the cost of building facilities, buying equipment and organising teleoperation teams,” said Poe Zhao, an independent China tech analyst and founder of Hello China Tech.

“But it also blurs the distinction between independent demand and demand created within a policy-supported ecosystem.”

Only a small share of the data is sold to non-robotics manufacturers such as carmakers for assembly line applications, training centre staff told the FT.

“This model can’t last,” said another investor. “If they fail to prove their robots can be deployed at scale on factory floors, investors will begin to reassess valuations over the next year.”

More than 90 training centres had been established or were being built across China by June, according to consultancy Interact Analysis. Leading centres said they generated more than 10mn data points a year.

Prices vary, but one seller told the FT that training data for a five-minute robot dance could cost as much as Rmb1mn ($148,000).

The training centre build-out is reshaping industry forecasts. Morgan Stanley raised its estimate for China’s humanoid robot shipments in 2026 to 50,000 units, from 28,000 in June, citing stronger than expected purchases by local governments and commercial users.

Supporters of the model argued it would help build up the country’s robotics industry and supply chain, noting the examples of electric vehicles and solar panels — sectors that China now dominates after government purchases drove initial demand.

For local governments, the model helps attract investment, talent and supply chains to areas where income from land sales has declined. Some training centres hire university students as robot trainers and offer paid tours for children and teenagers during school holidays.

For the robot makers and their suppliers, the training centres are a source of revenue amid limited commercial demand.

Shenzhen-based Leju Robot said training centres accounted for 45 per cent of sales of its flagship Kuavo humanoid last year, making them its largest revenue source.

UBTech disclosed Rmb140mn ($21mn) of orders from government-backed training centres last year. Although still lossmaking, the company said robot deliveries accounted for 41 per cent of its Rmb2bn revenue last year and expected government orders to drive further growth this year.

Almost three-quarters of Unitree’s humanoid robot revenue in the first nine months of 2025 came from users in the education and research sectors, including universities. Analysts said a relatively small proportion of shipments went to data collection centres.

Analysts said the close ties between local governments and robot makers made it difficult to distinguish genuine demand from policy-driven purchases.

“Companies like ours need revenue, not necessarily profits,” said an algorithm engineer at a Beijing-based company that sells software to robot makers. “The robot training centres can tell their superiors they’ve bought the equipment and robots, they’ve built data collection facilities and they’ve sold data.”

He added: “Both sides get what they need, and both sides have something to show.”

At Beijing’s largest robot training centre, where more than 100 Kuavo robots have been deployed, Leju owns almost 38 per cent of the operating company, according to registration records.

UBTech declined to comment. Leju and Unitree did not respond to requests for comment.

Another open question is whether the data generated justifies the investment.

Marco Wang, a Shanghai-based analyst at Interact Analysis, said training centre data was not going to be “100 per cent useful” because the robots were not deployed in real-world settings.

“The real-world application or real-world manufacturing line, real-world warehouse is always different from your scenario,” said Wang.

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Analysts at Goldman Sachs said scarce high-quality, real-world data remained the biggest hurdle to widespread adoption.

A senior manager at a training centre in northern China said each robot maker’s data could only be used by that company, raising concerns about compatibility.

She added that on average, only two or three hours of data from an eight-hour training shift were actually usable.

“China often accepts duplication and failed projects in the early stages of a strategic industry,” said Hello China Tech’s Zhao.

“The expectation is that technical learning, stronger supply chains and a handful of globally competitive companies may justify losses elsewhere.”