“We are also on the cusp of something really tremendous with Optimus, which I think is likely to be, has the potential to be, the biggest product of all time.”
Elon Musk, Tesla CEO, Q3 2025
Introduction
Over recent years, humanoid robots have made tremendous progress driven by advances in hardware and AI. Dozens of companies have entered the space and several are now moving from proof of concept toward mass production. The goal is to build machines that can take on physical labour, performing the dull, dangerous and dirty tasks that humans would rather avoid, both in factories and in households. If this vision can be achieved, many founders and analysts alike expect that over the long run there will be billions of humanoids on the planet, becoming as ubiquitous as cars and smartphones.
Yet the path ahead remains full of challenges. Most notably, general robotics has not yet been solved. Although today’s humanoids can perform demonstrations that look impressive, from dancing to doing backflips, they still struggle with tasks humans find trivial such as folding clothes. They also lack the general adaptability needed to operate reliably in unfamiliar environments. Ultimately, the ability to carry out practical real-world tasks while adapting to changing conditions and requirements will determine how widespread and impactful these robots can become.
In this note we first discuss the benefits of general-purpose humanoids and compare them with specialised robots. We then profile three prominent players in the space: Tesla, 1X and Figure AI. Next we examine the challenges humanoids must overcome to become truly general-purpose and reach scale. Finally, we outline the size of the opportunity and discuss how the emerging humanoid market could evolve.
The case for humanoid robots
There has long been debate over why general-purpose humanoids are needed when specialised machines can often perform individual tasks better. We agree that in many cases specialised robots will be superior and they are not going away. However, many of the tasks that need to be performed are varied, intermittent and carried out in conditions that change from moment to moment. Humans are still far better suited to this kind of dynamic work and that is exactly the type of role a humanoid is designed to take on.
A useful comparison is the smartphone, which combines voice calls, photography, gaming, payments and email into one device rather than relying on separate specialised equipment. While dedicated equipment might outperform it in specific areas, most people prefer the convenience of a single, versatile device over carrying multiple specialised ones.
Versatility can also be a direct advantage for certain tasks. For example, a robot vacuum cannot move a chair to clean under a table, whereas a humanoid can. In such scenarios the general-purpose solution is not only more convenient but also more capable.
Compared to specialised robots, humanoids can also be produced in much higher volumes given the potential demand, benefiting from economies of scale through in manufacturing and supply chains. Greater scale also spreads R&D costs across more units, driving down overall unit costs.
The human form factor is also an advantage. Most physical environments are designed around human proportions, so humanoids can naturally operate equipment and move through spaces built for people. In addition, the human form factor is far easier to train. Humanoids can learn directly from human demonstrations, including motion capture data, which provides high-quality examples of how tasks should be performed. Other form factors lack a human equivalent to learn from, making training significantly more difficult.
Tesla – Optimus
“Optimus, I think, probably achieves five times the productivity of a person per year because it can operate twenty-four seven.”
Elon Musk, Tesla CEO, Q3 2025
Optimus is Tesla’s humanoid robot and today roams parts of the company’s headquarters unsupervised. Musk has said it can guide visitors through the building and already performs some tasks inside Tesla’s factories. Optimus 2.5 was also publicly showcased at the Tron premiere in October 2025 where it demonstrated Kung Fu.
Figure 1: Optimus 2.5 doing Kung Fu at the Tron premiere in October 2025
Source: Youtube - DPCcars
It is difficult to know exactly how Optimus compares with its peers, as the field is currently in a fog of war. Afterall, most humanoids are not yet deployed widely in the real world and companies in the sector remain highly secretive about their latest capabilities. Many demonstrations rely on varying levels of teleoperation, which makes it hard to assess what is truly autonomous. Musk has commented that at least one of Optimus’s Kung Fu demonstrations was AI-driven rather than teleoperated, although the limited transparency in the sector still makes broader comparisons challenging.
Despite this limited transparency, Tesla remains widely regarded as a frontrunner in the humanoid race. Early investors and industry veterans with inside access to multiple projects consistently rank Tesla highly on technical grounds, even though their visibility is still partial. Additionally, Tesla’s extensive real-world AI experience, strong electrical and mechanical engineering capabilities and considerable manufacturing scale give the company a credible path to solving the field’s twin challenges of intelligence and manufacturing. Tesla is also well capitalised and led by a founder with an exceptional track record of tackling hard problems and creating value.
Tesla is now working on Optimus 3, which Musk describes as a giant improvement over Optimus 2.5. He has said they will probably unveil a production prototype in Q1 2026 and that it will seem like a person in a robot suit with agility roughly equal to an agile human. Scale production is now aimed to start at the end of 2026, though it will take a while to ramp up production.
“Optimus at scale is the infinite money glitch.”
Elon Musk, Tesla CEO, Q3 2025
The medium and long-term targets are highly ambitious. Optimus 3 is aimed at reaching 1 million units per year before 2030 at a target cost of less than US$20,000. Optimus 4 is planned to reach 10 million units annually with production starting in 2027. Optimus 5 is planned to reach 50-100 million units annually with production starting in 2028. Musk expects that humanoids will eventually account for 80% of Tesla’s value in the long run.
1X – Neo
A dark horse in this space is 1X, which was founded in Norway in 2014 and later relocated its headquarters to Palo Alto. In 2023 it raised US$23.5 million in a Series A2 round led by OpenAI, followed by a US$100 million Series B in 2024. It is now reportedly seeking a further US$1 billion, according to The Information.
Figure 2: Neo Home Robot by 1X
Source: 1X
1X gained considerable attention in October 2025 when it announced early-access pre-orders for its home robot, Neo. This is a lightweight humanoid designed to help with chores and act as a companion, allowing users to ask questions such as where they last left their keys. US deliveries are set for 2026, with early access priced at US$20,000 or US$499 per month.
Unlike most competitors, which target more industrial settings, 1X's focus on households presents greater safety challenges and far more environmental complexity. The company’s rationale for this, however, is that it believes consumer products scale much faster and that the variety of environments will deliver richer data, helping Neo improve more quickly.
Neo’s design centres on safety and lightness. Its finger strength matches that of a human, which is by design, because if it was excessively strong it would lose sensitivity. Instead of using traditional gear-based mechanisms commonly found in most robots, 1X has developed a proprietary actuation system called Tendon Drive, which uses high-torque motors pulling synthetic tendons inspired by biological muscles. This patented system enables smooth, quiet and safe movements while keeping the robot lightweight. It also makes the robot simpler and cheaper to produce, which has enabled 1X to already be able to manufacture Neo at an affordable cost.
Coinciding with the Neo launch announcement, the Wall Street Journal released a video interview with CEO Bernt Øyvind Børnich, showing Neo performing basic home tasks. It took around one minute to fetch a glass of water and roughly five minutes to load three items into a dishwasher. However, all demonstrations were revealed to have been conducted using teleoperations, where a human was in the loop helping the robot operate and make decisions. The video triggered an online backlash, as many felt the announcement was overhyped given Neo was not yet capable of acting autonomously.
“So when you get your Neo in 2026, it will do most of the things in your home autonomously. The quality of that work will vary and will improve quite fast as we get data.”
Bernt Øyvind Børnich, 1X CEO, October 2025 (WSJ)
Børnich explained however that the model shipping in 2026 will be more advanced than the one shown in the interview and mostly autonomous. Nevertheless, it will still rely to some degree on teleoperation or assistance from the owner’s voice commands for more challenging tasks. This will enable the robot to learn. Børnich reiterated that the version shipping in 2026 is meant for early adopters who understand the product is not perfect but insisted it will quickly become very useful. He has also noted that the Neo unit currently in his own home can autonomously retrieve a Coke from the fridge successfully around 50% of the time.
By 2027, 1X aims to ship 100,000 units, by which time Børnich expects Neo to be fully autonomous with no human in the loop. By 2028, he expects shipments to reach 1 million units, which is even more ambitious than Tesla’s target for Optimus 3.
Figure AI – Figure
Despite being founded in 2022, US-based Figure AI is already considered one of the frontrunners in the humanoid race. In September 2025, it raised over US$1 billion in a Series C round at a US$39 billion valuation with backers such as Nvidia, Qualcomm and Salesforce.
Figure 3: Evolution of Figure humanoids (Dreamforce 2025)
Source: Salesforce – Dreamforce 2025
Figure has also secured a notable commercial agreement. In January 2024 it signed a deal with BMW to bring its robots into automotive production. Reporting has been mixed on how much useful work the robots have actually been doing since the announcement. However, CEO Brett Adcock recently said that a robot has been operating autonomously for 10-hour shifts over the past five months and has now reached operational readiness.
Adcock had initially planned to focus on commercial/industrial applications before tackling domestic use. Over the past year however, his view has shifted and he now sees the home as a solvable challenge within a few years, possibly by 2026. He also insists they will not go to market using “silly” teleoperations like his competitors. Adcock also emphasised that adding a consumer focus will not come at the expense of their commercial efforts.
Currently, the company is on its third humanoid iteration, Figure 03, which was revealed in October 2025. In a Time profile, they witnessed Figure 03 successfully load items into a dishwasher but struggled with folding T-shirts. However, handling clothes and towels is one of the harder challenges for humanoids, given that fabric changes form upon interaction.
Unlike its predecessors, which were experimental prototypes, Figure 03 is engineered with cost and high-volume manufacturing in mind. Figure's dedicated manufacturing facility, BotQ, will initially be able to produce around 12,000 robots annually, with a goal of producing 100,000 units in total over the next four years.
Challenges ahead
“You have to … be able to like just talk to it and have it do anything you'd want it to do in unseen locations. That problem is not solved. That problem is 10 times, 50 times, 100 times harder than making a humanoid robot.”
Brett Adcock, Figure AI CEO, October 2025 (Nvidia GTC)
Despite humanoids seeing tremendous progress in recent years, major challenges remain. One persistent issue is the supply chain, as many of the components needed to build an advanced humanoid simply did not exist. This includes powerful motors, specialised sensors and more broadly, components with the durability to withstand continuous operation for many years.
Because a broader ecosystem has never really formed, companies have had to develop and manufacture a large portion of components themselves, forcing heavy vertical integration across the industry. As a result, humanoid companies are effectively building their own supply chains from scratch, a constraint that is likely to weigh on the industry for some time.
A further challenge is building a useful robotic hand and forearm. Several founders have highlighted that the hand is the hardest part of the humanoid to design because humans rely on them for almost every task and they require a huge range of precise, coordinated movements. Without a truly capable hand, even advanced humanoids will struggle with a wide range of basic tasks.
Beyond hardware, humanoid robots also face regulatory uncertainty, particularly for domestic applications. Governments will need to establish safety standards, liability frameworks and potentially certification processes before widespread home deployment can occur. Data privacy and cybersecurity present further concerns as robots with cameras, microphones and internet connectivity operating in homes could become targets for hacking or surveillance, raising questions that manufacturers have yet to fully address publicly.
Perhaps the most significant challenge, however, is developing general-purpose robotic systems. Adcock views this as the primary bottleneck, far outweighing manufacturing constraints. A key limitation today is the scarcity of high-quality real-world data for training, which companies are now trying to address in different ways. Figure plans to allocate much of its recent US$1 billion funding to hiring humans for first-person video data collection, while 1X intends to gather much of its data from its early-access Neos shipping in 2026.
However, experts question whether feeding models more data alone will suffice. Meta's Chief AI Scientist and renowned ML expert, Yann LeCun, has warned that current approaches may excel at specific tasks but fall short of true generality (the ability to handle open-ended tasks and unfamiliar situations) without fundamental breakthroughs:
“The big secret of the industry is that none of those companies has any idea how to make those robots smart enough to be useful. Or I should say, smart enough to be generally useful.”
Yann LeCun, Meta Chief AI Scientist, October 2025 (MIT)
Legendary programmer John Carmack echoes this scepticism:
“I am more skeptical than a lot of people in the tech space about the near term utility of humanoid robots. Long term, driven by AGI, sure, they are going to be an enormous economic engine, but business plans that have them making a dent in the next five years seem unlikely.”
John Carmack, November 2024 (X)
The founders themselves remain more optimistic. Musk has highlighted a potential breakthrough threshold that he thinks Tesla can achieve, where Optimus would learn new tasks simply by watching YouTube or how-to videos, much like a human. Meanwhile, Adcock and Børnich believe fully autonomous general-purpose humanoids are just two years away. Time will tell whether more data can overcome today’s limits, or if progress stalls until deeper AI breakthroughs arrive.
The humanoid market
“There will be more humanoids on the planet than there are people. There's absolutely no doubt about that. At least everyone wants a humanoid, but you want way more than that.”
Bernt Øyvind Børnich, 1X CEO, October 2025 (The Casey Adams Show)
CEOs of humanoid companies forecast massive TAMs, expecting billions of units in the long run. Adcock sees this as a roughly US$40 trillion opportunity, essentially all the labour in the current global economy. These companies attribute this scale to broad adoption across many sectors, from industry to the home, driven by the promise of cheap, flexible labour. Demand will also be supported by the ageing population, as labour shortages intensify and humanoids are needed to assist with elderly care.
Yet ubiquity will take time. Even if general-purpose humanoids arrive tomorrow, creating the infrastructure to manufacture billions of units will be challenging and likely encounter multiple issues that need to be solved. This includes potential regulatory hurdles and component shortages (e.g. chips). Additionally, most consumers currently cannot afford a US$20,000 robot and therefore prices would need to come down or income per capita would need to rise substantially.
Morgan Stanley estimates that by 2050 there will be nearly 1 billion humanoids, with 90% in industrial and commercial use cases, representing a US$4.7 trillion market.
Figure 4: Long-term forecast of humanoid revenue
Source: Morgan Stanley Research
This is similar to Bank of America’s forecast, which expects just over 1 billion humanoids by 2050 and 3 billion by 2060. However, unlike Morgan Stanley, it expects household robots to make up the majority of units. This reflects the uncertainty of how the industry will evolve.
Figure 5: Long-term forecast of humanoid units
Source: Bank of America Research
“What matters is shipping a product at scale that can generate the data to increase intelligence and reduce cost. That's who wins in my mind. Like who's the first through a million robots in market? That's a big marker that will help determine like the leader.”
Brett Adcock, Figure AI CEO, November 2025 (WTF Online – Nikhil Kamath)
What also remains unclear is the future market structure, whether it will be fragmented or dominated by a few players. Many factors will shape the outcome, though one key factor could be a data moat. Adcock has argued that humanoid robotics could become a natural monopoly, as each additional robot deployed generates real-world data that improves all others. This creates a powerful flywheel: the leader in deployed units gains a growing data advantage, enabling smarter robots, driving more sales and widening the gap with competitors.
Yet this outcome is not guaranteed, as it depends on whether additional data continues to yield meaningful improvements or eventually flattens out. Future models may also require less data to learn, which could reduce the advantage of scale.
“We are not in a race against China… it doesn't matter if China makes a million humanoid robots tomorrow. They just don't work very well to be frank.”
Brett Adcock, Figure AI CEO, November 2025 (WTF Online – Nikhil Kamath)
Geographic leadership is also debated. Many have argued that China will have a distinct advantage due to its manufacturing capacity. Adcock downplays this, arguing that Chinese humanoids are nowhere near Figure’s capabilities and that manufacturing is not the main bottleneck. He also argues that manufacturing robots will be significantly easier than manufacturing cars as he sees humanoids as being more akin to consumer electronics products.
However, Tesla's own well-documented manufacturing challenges with vehicles, despite Musk's expertise, and acknowledging the complex nature of humanoid systems, suggests that scaling production to millions of units annually may prove more difficult than Adcock anticipates, particularly given the need for vertical integration across novel supply chains.
Ultimately, we see humanoid robots becoming a multi-trillion-dollar market, but forecasting unit volumes or market share with any precision remains difficult given the uncertainty around future AI breakthroughs. However, much of the current fog of war should begin to lift in 2026 as companies move from prototypes into mass production and robots start appearing more frequently in real-world settings. At that point, we will gain a clearer sense of how the market is likely to evolve.
Conclusion
Humanoid robotics stands on the brink of shifting from science fiction to economic reality. The abundance of cheap labour would be transformative to the global economy, substantially reducing the cost of goods and services, with some like Musk believing it could even abolish poverty. Yet the path ahead remains steep and uncharted. True general-purpose autonomy is still unsolved and the manufacturing challenge will be immense. However, the companies leading this charge are well capitalised and technically formidable. Over the next five to ten years, humanoid robotics will likely be one of the most exciting fields in technology, with rapid iteration and fierce competition that could ultimately give rise to the next generation of economic giants.
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