Humanoid Robotics Gold Rush Raises AI Bubble Fears as Investors Warn of Collapse

Investors warn humanoid robotics hype inside the AI boom is outpacing revenue, reliability and real-world deployment

The rush of investing money into artificial intelligence is getting into a new and potentially dangerous phase, with humanoid robotics coming out as the latest darling of venture capital.

Latest investment data says that interest in humanoid robots is accelerating faster than almost any other AI category. But behind the glossy demos and big promises, experts are warning that the sector may be moving towards a dangerous bubble.

Why Investors Fear Humanoid Robotics is Becoming AI's Next Bubble

Top venture capital reports from firms such as KPMG and PitchBook have said that AI continues to rule global investment, accounting for more than half of all deals this year. Now, within those AI investment areas, however, it is industrial humanoid robotics that is getting the most attention, it seems.

Moreover, data from CB Insights shows that last quarter itself saw 17 deals in industrial humanoid robotics, which is the highest number for any AI category during that time. By comparison here, other popular segments such as coding AI agents and copilots got 14 deals, while end to end software development agents attracted 12 of them.

Now, investors point out that this giant change is happening less because of proven demand and more because of the belief that advanced AI has finally made humanoid robots commercially viable. It seems that, for years, humanoid machines were seen as impressive engineering projects with little practical use. Today, though, breakthroughs in perception and language models have increased hopes that robots could eventually perform human-like work in factories, warehouses, and even in public.

It is that optimism that has got experts actually worried. According to CB Insights, many humanoid robotics startups face massive structure-based challenges around cost and real world performance. These problems are not easily solved and could take years to overcome. Still, valuations are rising high as if commercial deployment were just around the corner.

Furthermore, warnings are not limited to Western investors, as China's leading economic planning bodies have asked the humanoid robotics industry to balance this super growth against the risks of bubbles, according to reports by Bloomberg. The main worry is that too many companies are promising breakthroughs without providing evidence that customers are willing to pay for them at that scale.

Daiva Rakauskaitė, a partner and manager at Aneli Capital, sees uncomfortable parallels with the dotcom boom of the early 2000s. She believes many AI startups that cannot yet generate money in terms of revenue will fail and expects an AI bubble to burst within the next two to three years. Now, while that risk is getting acknowledged in software driven AI sector, she points out that investors are overlooking similar dangers in humanoid robotics.

Additionally, an important distinction, she says, lies between robotics as a whole and humanoid robotics specifically. Industrial and logistics robots already generate revenue and deliver measurable efficiency gains. Humanoid robots, though, still have to prove their commercial value beyond controlled demos.

Reality Check for Humanoid Robotics Startups

Around the world, humanoid robotics companies regularly show eye catching prototypes capable of running, lifting weights or even boxing, and videos of these go viral often. These demonstrations get a lot of attention from investors and the public as well, backing up the idea that a robotics revolution is coming immediately. However, experts again warn that such demos rarely turn into profitable business models.

Moreover, even in industrial areas, humanoid robots face many limitations. CB Insights points out ongoing problems with real-time inference, physical dexterity, long-term reliability and cost. As a result, their potential use cases are for now restricted to highly predictable environments such as factories and warehouses, where tasks are repetitive and tightly controlled. Outside those settings, performance quickly degrades it seems.

Furthermore, cost remains another giant and scary fault line. Humanoid robots are expensive to build, maintain and repair. So, for most companies, deploying them at a massive scale would require costs to fall a lot, while reliability would need to improve to levels comparable with existing industrial automation. Experts warn that these hurdles will not be cleared in the near future at all.

Rakauskaitė argues that this is exactly why venture capitalists should return to the fundamentals of revenue-first philosophy, as she says.

'Investments in robotics and AI are crucial for the future development of humanity. But investors should remain disciplined and back companies that have realistic goals based on economics, not hype. From day one, startups should aim for early revenue streams through licensing, partnerships and have a clear model of monetization in the near future. The same revenue-first philosophy can be applied to any field.'

Importantly, she stresses that this does not mean abandoning robotics or AI investment altogether, as she is optimistic still about the sector, but her point is that the danger lies in conflating long-term potential with immediate commercial readiness.

Finally, Central and Eastern Europe, she says, is especially well-positioned to benefit from realistic robotics investment. This is because of its proximity to Germany, Europe's largest industrial robotics market, giving huge advantages for scaling.