Chinese automakers’ efforts to enter the humanoid-robot market are accelerating, in a bet that goes beyond product diversification to seek a new source of profit away from the narrow margins of the automotive industry. Xpeng stands out as the company most closely associated with this trend after its robotics unit raised more than $900 million, reaching a post-money valuation exceeding $6.3 billion.
IDG Capital led the round, with participation from Gaorong Ventures, Tencent and Alibaba. The company described it as the largest single private funding round on record in China’s “embodied artificial intelligence” sector, meaning systems that integrate artificial intelligence directly into physical machines. Xpeng is targeting the commercial development of its Iron humanoid robot, while reports said that Chery Automobile’s AiMOGA unit had begun preparing for an initial public offering.
A Push That Goes Beyond One Company
The wave is not limited to Xpeng and Chery. BYD has unveiled a humanoid robot called Xiao Di, while Changan, GAC, Li Auto, SAIC and Seres are developing their own humanoid robots. This comes as improvements in robots’ physical capabilities have strengthened the belief that the learning technologies used in large language models could help machines learn a wide range of complex tasks.
Michael Dunne, chief executive of consulting firm Dunne Insights, believes Xpeng is closely following Tesla’s initiatives, and that its founder, He Xiaopeng, views robotics as a more promising opportunity than the automotive market, which offers limited profits in the near term. According to The Wall Street Journal, Xiaopeng and the company’s co-chairman, Brian Gu, invested about $100 million of their own money in the latest funding round.
What Do Automakers Actually Have?
The clearest advantage of Chinese automakers is their manufacturing expertise and the infrastructure needed to handle hardware, which could help them produce robots or scale up their production. But this advantage does not settle the competition; the question Dunne raises is whether these companies can keep pace with Tesla in artificial intelligence.
This is where the gap lies between manufacturing an advanced vehicle and building a robot capable of understanding a changing environment and safely and reliably performing diverse tasks. The article points to ambition, funding and advances in models, but provides no evidence of widespread commercial deployment or of any of these companies’ ability to achieve stable operating economics.
Global Competition Enters the Factories
The race is not limited to China. Agility Robotics, Apptronik and Figure are developing humanoid robots with the aim of achieving large-scale commercial use. Boston Dynamics, owned by Hyundai, is approaching this goal; Hyundai plans to introduce the Atlas robot into its factory in the state of Georgia during this year, and then use it for tasks such as sorting parts by 2028.
Hyundai is also collaborating with Google’s DeepMind laboratory to accelerate Atlas’s development, and is opening a facility in the United States this year called the Robot Metaplant Application Center to teach robots movements such as lifting and turning. In another direction, Mobileye acquired humanoid-robotics startup Mentee Robotics for $900 million, while Rivian is working on the Mind Robotics project, although its robots are not expected to take the same humanoid form.
Why Does This Shift Matter?
The entry of automakers into humanoid robotics transforms the field from an experimental area led by specialized companies into a potential extension of an industry with expertise in motors, sensors, supply chains and large-scale production. For the technology reader, this means that future competition will not revolve only around the robot’s form, but around who can combine hardware, data and software into a reliable, deployable system.
But large funding rounds and announcements about models alone do not answer the decisive questions: Which commercial tasks will actually succeed? When will the cost of operating a robot become acceptable? And can automakers develop the artificial intelligence they need as quickly as they expand their manufacturing capabilities? These questions remain open in the article, so the current bet reflects growing confidence in the market more than it proves that the market has reached commercial maturity.