Venture funding to robotics startups reached $9.9bn in the third quarter of 2026, more than double the $4.3bn recorded a year earlier, according to Crunchbase data. The surge is part of a broader funding rise for robotics, with China and the US taking the largest reported shares.
Watch Desk analysis
What happened
Crunchbase reports that robotics funding across the first three quarters of 2026 was up about 185% year on year. It puts investment in Chinese robotics companies at $13.2bn and in US companies at $12.1bn, compared with $1.7bn in Germany.
Among the largest reported rounds were $1.4bn for US robotics foundation-model developer Skild AI, $900m for China’s Xpeng Robotics and $736m for China’s AI² Robotics. The figures and company descriptions come from Crunchbase’s funding analysis, which says its analysis excludes defence-related companies.
Why it matters
These numbers suggest that investors are backing more than robot hardware: the article also describes competition over the data and models needed to make machines work in the physical world. Encord co-CEO Ulrik Stig Hansen told Crunchbase that physical AI requires collecting and processing far more varied data, including vision, touch, force and torque. That infrastructure is expensive, and unlike text for language models, physical-world data cannot simply be gathered from the internet in the same way.
The money is not proof that these companies will deliver useful robots or durable returns. But the scale and spread of the reported rounds make this a meaningful signal of investor appetite, not just another robot promising to fold laundry eventually.
Our read
The standout is the breadth: big funding is flowing into companies pursuing different parts of robotics, from models to applications. The data-and-model layer may prove as important as the machines themselves, but it will need to turn capital into systems that work beyond carefully managed demonstrations. Crunchbase’s figures offer a useful snapshot of where investors are placing their bets, not a scorecard of which bets will pay off.
What to watch
- Whether the funded companies publish evidence of robots working reliably outside controlled settings.
- Whether the data and compute costs of physical AI can support sustainable businesses.
- How funding and company growth compare across China, the US and other robotics markets.
Discussion spark: Should physical AI funding go first to general-purpose robot models and data infrastructure, or to specific robots that can prove a real use case?
Sources and evidence
- Source update (27 October 2026, 11:00 UTC)
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