But behind the numbers, one question stands out: is Figure AI building something fundamentally new, or is it reproducing the hype cycle we have come to know with generative AI?

The honest answer is: probably both at once. And that is precisely what makes this company so fascinating to study.

From zero to $39 billion in three years: the journey

Brett Adcock is not a robotics engineer by training. He is a serial entrepreneur, founder of Vettery, a tech employment marketplace sold to Adecco, and Archer Aviation, an electric air taxi company. Two very different sectors, but one constant: long-cycle, capital-intensive markets where the race for resources matters above everything else.

In 2022, he launched Figure AI with a simple and radical conviction: the global labor market is short of hands. Physical, repetitive and demanding tasks handling, logistics, industrial assembly are becoming increasingly difficult to fill in developed countries. A humanoid robot capable of performing these tasks without redesigning existing production lines would represent a market opportunity potentially larger than the automotive industry itself.

The bet quickly attracted some of the biggest names in tech. In 2024, Figure closed a $675 million Series B round at a valuation of $2.6 billion, with Microsoft, NVIDIA, the OpenAI Startup Fund, Jeff Bezos through Bezos Expeditions, Intel Capital and ARK Invest. The list of investors is almost as impressive as the machines themselves. In September 2025, an additional $1 billion Series C round brought the valuation to $39 billion, with Brookfield Asset Management and Macquarie Capital joining the table alternative asset managers that do not invest in science fiction.

In eighteen months, the valuation increased fifteenfold. That is rarely seen, even in tech. A new funding round is reportedly being prepared for 2026–2027.

Figure 01, Figure 02, Figure 03: three generations, one philosophy

Figure’s product trajectory is fast and methodical, which sets it apart from many robotics startups that produce demo after demo without ever leaving the laboratory.

Figure 01, was the founding prototype, presented in 2022. A bipedal robot measuring 1.67 meters and weighing 60 kilos, capable of walking and grasping objects. Not enough for a real production line, but enough to raise funds and demonstrate a direction.

Figure 02, launched in August 2024, represents the company’s first real industrial deployment. This was the robot sent to BMW’s assembly plant in Spartanburg, South Carolina and that is not a minor detail. For eleven months, Figure 02 worked ten-hour shifts, Monday to Friday, on a clearly defined task: loading sheet metal parts onto welding fixtures. In total, it completed more than 1,250 hours of real operation, loaded more than 90,000 parts, and reportedly contributed to the production of more than 30,000 BMW X3 vehicles.

That is the number that changes everything. You can manufacture beautiful laboratory videos. You cannot so easily manufacture 30,000 cars.

Figure 03, launched in October 2025, marks a philosophical turning point. The third generation is designed for two environments at once: industry, of course, but also the home. Soft exterior covering for safer human contact, wireless charging, redesigned audio interface, 44 degrees of freedom, tactile sensors capable of detecting forces from as little as three grams precise enough to handle an egg without breaking it.

On the hardware side, the wrist architecture was completely redesigned after BMW’s feedback: the motor controllers now communicate directly with the main computer, without an intermediate distribution board, improving reliability and simplifying thermal management. These are the details that distinguish an engineering robot from an industrial robot.

In March 2026, Figure released a video of Figure 03 autonomously tidying up a living room picking up toys, putting cushions back in place, wiping a table, restoring order. The movements are not fast. But they are continuous, natural, and the robot adapts to the changing layout of objects. This is no longer just a laboratory demonstration.

Helix is based on a logic close
to generative AI models: learning
massively through experience

Helix: the brain that makes all the difference

Figure’s hardware is solid. But what truly interests engineers, investors and competitors is Helix the AI model developed entirely in-house, which forms the central nervous system of all Figure robots.

Helix is a Vision-Language-Action model, or VLA. This type of architecture is at the heart of the new generation of intelligent robotics. In practical terms, the robot receives images from its cameras and instructions in natural language, and the model directly produces motor commands. No multi-step pipeline, no spatial segmentation followed by trajectory planning and then execution everything is integrated into a single neural network that sees, understands and acts.

What makes Helix particularly remarkable is that it runs onboard, without relying on the cloud. Figure 03 carries up to two NVIDIA GPUs per unit. Processing is local, eliminating the latency and connectivity issues that would penalize an industrial robot in a real environment.

Helix 02, presented in January 2026, extends this control to the robot’s entire body walking, manipulation, balance all driven by a single unified neural network. The living room demonstration is the direct consequence of this: the robot is not following a script. It observes its environment, identifies objects, plans and executes actions in real time.

This is what Brett Adcock calls the shift from the “programmed” robot to the “learning” robot. The difference is not cosmetic it is architectural. A programmed robot will only ever execute what it has been told to do. A robot driven by a sufficiently trained VLA can, in theory, approach a new task without reprogramming.

The challenge of scaling production: BotQ and Project Go-Big

Developing a humanoid robot capable of working in a factory is one thing. Manufacturing thousands then millions is another matter entirely. This is precisely where many robotics startups hit the wall: industrialization.

Figure anticipated this problem by building BotQ, its dedicated humanoid robot manufacturing facility. The production philosophy changed fundamentally between Figure 02 and Figure 03. While the previous generation relied on CNC machining for most mechanical parts precise but expensive Figure 03 is designed for die casting, plastic injection molding and stamping. These processes require heavier upfront investment, but they reduce unit costs as volumes increase. This is classic industrial logic: invest heavily in capex to reduce variable costs.

At the same time, “Project Go-Big” is a large-scale data collection initiative designed to feed Helix’s training. The more robots operate in real-world conditions, the more the model learns from varied situations, and the more capable it becomes. Field data is the scarce resource in humanoid robotics and Figure has understood that producing it at scale is a durable competitive advantage.

The real challenge in humanoid
robotics is no longer creating a
functional robot, but producing
it at scale

What Figure has not yet proven

An honest analysis of Figure AI must name the grey areas and they do exist.

The $39 billion valuation is built on potential, not on revenue. Figure’s current revenue remains limited. The BMW deployment is a pilot, not a mass-production contract. BMW and Figure are still evaluating additional use cases for Figure 03, and BMW’s March 2026 press release remains cautious about future commitments.

In June 2025, Brett Adcock declined to do a live demonstration at a major tech conference and refused to publicly answer detailed questions about the reality of the BMW partnership. This is not an alarming signal in itself startup CEOs often avoid uncontrolled demos but it is a useful reminder that the distance between a carefully controlled video and a stable industrial production line remains real.

The comparison with Tesla Optimus is inevitable and deserves to be taken seriously. Tesla is targeting a price range of $20,000 to $30,000 per unit, with ambitions to produce millions of units at scale. The Fremont factory, repurposed for Optimus, is already targeting 12,000 units per year in its initial phase. Figure has not announced a public price for Figure 03, nor a short-term production volume target. On this commercial and industrial front, Tesla has strengths that Figure has not yet demonstrated.

Chinese competition also deserves a mention one that too few Western articles take seriously. Around 90% of humanoid robots sold worldwide in 2025 were designed by Chinese companies, according to the International Federation of Robotics. UBTech, Unitree, Fourier Intelligence and XPeng operate with structurally different production costs. The price war in humanoid robots has not yet begun but it will come.

Who is the CEO of Figure AI?

Brett Adcock is an American entrepreneur specialized in breakthrough technologies and artificial intelligence. Before launching Figure AI in 2022, he had already co-founded Archer Aviation, a company developing electric flying taxis.

With Figure AI, Brett Adcock aims to create humanoid robots capable of working in factories, logistics warehouses and, eventually, homes. His stated goal is to develop a new generation of general-purpose robots capable of performing repetitive, physical or dangerous human tasks using artificial intelligence.

In just a few years, Figure AI has become one of the most closely watched startups in the humanoid robotics sector. The company is working on robots capable of sorting parcels, handling objects, cleaning spaces and assisting industrial operators. Several recent demonstrations have attracted millions of views online, particularly videos showing robots completing full autonomous logistics sorting shifts.

For many analysts, Figure AI is now among the most advanced companies in the global race for humanoid robots, alongside Tesla with Optimus and Agility Robotics.

What Figure AI says about the state of the sector

Figure AI is not an isolated story. It is the sign of a specific moment in the history of robotics.

For the first time, several technologies are maturing simultaneously: language models powerful enough to understand complex instructions, onboard GPUs compact enough to fit inside a robot torso, force and vision sensors precise enough for fine manipulation, and supply chains mature enough to make scaled production imaginable.

This was not true in 2015. It was not really true in 2020 either. In 2025–2026, the conditions are coming together for humanoid robots to move from the laboratory to the factory. Figure AI is one of the companies making that transition tangible.

For industrial leaders reading these lines, the question is not yet: “Should I buy a Figure robot?” It is: “Should I follow this technology closely, understand its real capabilities, and prepare for possible integration over the next three to five years?”

The answer to that question is yes with the caution required for any long-term bet on a technology still under development, but also with the attention that a true paradigm shift deserves when it begins to happen.

Robot Magazine follows the evolution of industrial humanoid robotics. Figure AI, Optimus, Boston Dynamics Atlas: the field is taking shape quickly. Next article in this series: the technical showdown of industrial humanoids in 2026.

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Its name: “Physical AI”, or physical artificial intelligence.

Behind this concept, still relatively unknown to the general public, lies what some investors already consider to be the next major technology cycle after the internet, cloud computing and generative AI.

The idea is simple but potentially revolutionary: enabling artificial intelligence to interact physically with the real world through robots, autonomous machines, smart factories and systems capable of seeing, understanding, moving and acting.

And the amounts being invested are already giving a sense of the scale of the phenomenon.

According to several specialized research firms, the global market for intelligent robotics and Physical AI could exceed $3 trillion by 2040 if humanoid robots, autonomous factories and robotic systems truly become widespread across industry and services.

For investors, the question is no longer whether this market will emerge, but rather which companies will become the future giants of this new economy.

The potential IPO of SpaceX could create a mixed reaction for Tesla shares. In the short term, some investors could shift part of their Tesla positions in order to gain direct exposure to SpaceX, considered one of the most strategic technology assets in the world. But in the medium term, the development of Tesla’s humanoid robot Optimus could, on the contrary, strengthen Tesla’s valuation by gradually repositioning the group as a global leader in Physical AI and robotics, beyond the automotive market alone.

For investors, “Physical AI” could become a market even larger than electric vehicles. According to Goldman Sachs, humanoid robots could represent more than $150 billion by 2035, while the broader intelligent robotics market could exceed $400 billion. Driven by labor shortages, industrial automation and the rise of AI, this sector is already attracting massive amounts of capital, with players such as NVIDIA valued at more than $3 trillion in 2026.

A historic transition: AI moves beyond screens

Since 2023, generative artificial intelligence has deeply transformed technology markets. OpenAI, NVIDIA, Microsoft and Google have seen their valuations soar thanks to the democratization of language models.

But until now, this revolution has remained essentially digital.

AI was producing:

• Text
• ImagesVideos
• Code
• Analysis

Physical AI completely changes the game.

For the first time, artificial intelligence is leaving screens and entering the physical world.

The new systems developed by industrial companies and startups now aim to create machines capable of manipulating objects, moving around, interacting with humans, analyzing their environment and performing physical tasks autonomously.

In other words, AI is gradually becoming a workforce.

And that is precisely what is now attracting the attention of financial markets.

NVIDIA: the silent winner of Physical AI

If there is one company today already benefiting massively from the rise of Physical AI, it is probably NVIDIA. After dominating the generative artificial intelligence market through its GPUs, the group is now accelerating strongly in humanoid robots, autonomous vehicles, smart factories, industrial simulations and computer vision.

Its CEO, Jensen Huang, now openly describes “Physical AI” as the next massive market for artificial intelligence. And the numbers are already staggering: NVIDIA’s market capitalization surpassed $3 trillion in 2026, making the group one of the most powerful companies in the history of technology.

This dominance can be explained by a positioning that has become almost unavoidable. Today, a large share of intelligent robotics players use NVIDIA GPUs, CUDA platforms, Omniverse simulation tools and embedded systems developed by the group. NVIDIA is therefore gradually becoming the central infrastructure of the new global robotics economy, just as the internet and cloud computing were for previous technological revolutions.

Figure AI: the humanoid startup fascinating Silicon Valley

Among the most closely watched companies today is Figure AI.

Still unknown to the general public not long ago, the company is now attracting attention across Silicon Valley.

The reason?
Figure AI is developing humanoid robots capable of performing physical tasks in:

Warehouses, logistics, factories and supply chains.

But what impresses investors most is the financial backing behind the project.

The company is backed by Microsoft, OpenAI, NVIDIA and Jeff Bezos.

According to several American financial media outlets, Figure AI has already reached a valuation of several billion dollars even before a possible IPO.

The humanoid robot sector is therefore beginning to reproduce what the market experienced with generative AI startups between 2023 and 2025.

While the world is talking about ChatGPT,
another, much deeper revolution
may already be beginning.

China is accelerating massively

While Western media focus on American giants, China is moving very quickly in intelligent robotics.

The Chinese government now considers humanoid robots a strategic priority sector.

According to Chinese authorities, the country aims to become one of the global leaders in the sector before 2030.

And several companies are rapidly gaining momentum.

Unitree Robotics is attracting particular attention thanks to its humanoid and quadruped robots, which are offered at far more aggressive costs than their Western competitors.

Other players such as UBTech, Fourier Intelligence and Xiaomi are now investing heavily in:

• Sensors
• Batteries
• Robotic components
• Autonomous systems

China already has considerable advantages: industrial power, access to components, battery expertise, massive production capacity and an integrated supply chain.

As with electric vehicles, Beijing appears determined not to miss the next technological revolution.

Historic industrial players are already preparing their autonomous factories

But startups are not the only ones accelerating in Physical AI. Major legacy industrial groups are also investing heavily in factory transformation and intelligent automation.

Siemens is strongly developing its activities around digital twins, smart factories, industrial automation and predictive AI. The German group is now betting on factories capable of optimizing their own production using data, smart sensors and artificial intelligence.

ABB, meanwhile, remains one of the global leaders in industrial robotics, with a major presence in automotive, logistics, energy and automated production lines. The group is now investing heavily in collaborative robots and industrial intelligence systems capable of improving the flexibility of modern factories.

The same momentum can be seen at Teradyne, owner of Universal Robots, considered the global leader in cobots. These collaborative robots, capable of working alongside humans, are experiencing particularly rapid growth among industrial SMEs and flexible production lines.

According to several sector studies, the global cobot market could exceed $20 billion before 2030, driven by the search for productivity, labor shortages and the acceleration of industrial automation.

Case study: Amazon warehouse automation

One of the best examples of this transition toward Physical AI is probably logistics.

For several years, Amazon has been accelerating the automation of its warehouses by relying on mobile robots, artificial intelligence systems, machine vision and advanced logistics algorithms. The group reportedly now has more than 750,000 robots deployed in its logistics centers around the world.

The objective is clear: reduce delivery times, improve productivity, offset recruitment challenges and optimize operating costs.

Amazon is now experimenting with even more advanced technologies combining generative AI, autonomous robots and intelligent object manipulation in order to make its infrastructure increasingly flexible and automated.

This technological model is now inspiring much of the global logistics sector and represents precisely the type of environment targeted today by startups specializing in humanoid robots.

A response to the global labor shortage

Behind the technological enthusiasm lies a much deeper economic reality.

Demographic aging is now affecting Europe, Japan, South Korea, China and, gradually, several Western economies.

In certain sectors such as industry, logistics, healthcare, maintenance and services, industrial companies are already facing increasing recruitment pressure. In many developed countries, population aging, the decline in the number of qualified technical profiles and the rapid transformation of jobs are creating a structural labor shortage.

In sectors such as logistics, industrial maintenance, automotive, automated warehouses and manufacturing, companies are finding it increasingly difficult to recruit operators, technicians and engineers capable of working in advanced technological environments. According to several international studies, several million industrial jobs could remain vacant in the coming years due to a lack of available qualified talent.

This situation is gradually pushing industrial players to accelerate their investments in intelligent automation. New-generation robots are no longer designed only to replace repetitive tasks on fixed production lines. Thanks to recent progress in artificial intelligence, computer vision and smart sensors, these systems are gradually becoming capable of adapting to complex environments and collaborating with humans.

In this context, intelligent robots appear to be a potential long-term economic solution for offsetting certain labor shortages, improving productivity and maintaining industrial competitiveness. Although the market is still young and technologically in a phase of acceleration, many industrial players already consider Physical AI to be one of the possible answers to the structural challenges of the global labor market.

Logistics is becoming one of the
first testing grounds
for Physical AI.

Is the market already in a bubble?

As with every technological revolution, valuations are already beginning to raise questions.

Some humanoid robot startups are worth several billion dollars despite still having very limited revenues.

Humanoid robots remain extremely complex from a technological standpoint:

• Autonomy
• Safety
• Balance
• Understanding the real world
• Fine manipulation

Large-scale economic use cases have not yet been fully validated.

But history also shows that major revolutions often begin during phases of speculation:

• The internet
• Cloud computing
• Electric vehicles
• Generative AI

Physical AI now seems to be entering this same dynamic.

A revolution that could last several decades

Unlike certain technological trends, Physical AI directly affects:

• Industry
• Infrastructure
• Logistics
• Healthcare
• Transport
• Global productivity

In other words:
Physical AI is no longer only about laboratories or software; it now directly affects the real economy.

And that is precisely what fascinates investors so much. For the first time, artificial intelligence may no longer simply assist humans with intellectual or digital tasks.

Through intelligent robots and autonomous systems, it could also act physically in the real world: moving goods, assembling products, building, assisting operators or automating certain complex industrial tasks. For many analysts, this convergence between AI and robotics could profoundly transform the global economy over the next twenty years.

“Physical AI” is no longer simply a futuristic concept reserved for research laboratories: it is gradually becoming a new strategic global market at the crossroads of artificial intelligence, robotics, automation, semiconductors and industrial infrastructure.

Companies such as NVIDIA, Figure AI, ABB, Siemens and Unitree Robotics are already among the players most closely watched by the markets.

And even though the sector remains young and speculative, one thing now seems clear: the next great revolution in artificial intelligence could be physical.

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For a long time, Tesla was seen as the company that would revolutionize the automotive industry. Elon Musk’s company disrupted the electric vehicle market, pushed traditional carmakers to accelerate their energy transition, and transformed the car into a connected software platform.

But over the past several years, a profound shift seems to have been taking place at Tesla. Elon Musk is talking less and less about cars, and more and more about artificial intelligence, autonomy, and above all, humanoid robots.

At the heart of this new vision is Optimus, the humanoid robot developed by Tesla. A project that, only a few years ago, seemed almost unrealistic. Today, it has become central to the group’s strategy.

For some investors, Optimus could represent the largest market in Tesla’s history. For others, it remains an extremely speculative technological promise designed to support the group’s stock market valuation.

But another question is now beginning to emerge on Wall Street: what if SpaceX ultimately became the most strategic asset in the Musk empire? Could a potential SpaceX IPO divert some of the investors currently positioned in Tesla?

Behind these questions lies a much deeper transformation. Elon Musk no longer seems to want to build only cars. He now appears to want to build the technological infrastructure of the future.

Optimus: Tesla’s most ambitious bet

When Tesla first unveiled Optimus, many saw the presentation as just another marketing move. The market was still focused on electric vehicles, batteries, and autonomous driving.

But over the past two years, the signals have multiplied. Tesla has been investing heavily in recruiting engineers specialized in robotics, computer vision, and artificial intelligence. Technical demonstrations have followed one another. And above all, Elon Musk has repeatedly stated that Optimus could become “Tesla’s most important product.”

That statement may sound surprising when referring to a company that already sells millions of electric vehicles around the world.

Yet Musk’s logic is relatively simple: the humanoid robot market could become infinitely larger than the automotive market.

Tesla imagines a future in which humanoid robots could gradually take over repetitive physical tasks in:

• Factories
• Warehouses
• Logistics
• Services
• Even homes

In other words, Optimus would not be aimed only at industry. Tesla seems to want to create a universal robotic platform capable of evolving in environments designed for humans.

And this is precisely what distinguishes humanoid robots from traditional industrial robots.

Tesla could gradually reduce its dependence on automobiles

This is probably one of the most underestimated scenarios on the market today.

Tesla is still officially an automaker. But several analysts are beginning to believe that, in the medium term, the company could gradually reduce its dependence on car manufacturing and invest more heavily in:

Artificial intelligence , Robotics, Software and Automation

Why?

Because the automotive market is becoming increasingly competitive.

China is accelerating massively with BYD, Xiaomi, NIO, and Xpeng. Traditional European and American manufacturers are also investing billions in electric vehicles. Margins are starting to shrink. Prices are falling. And the electric car could gradually become an industrial commodity.

In this context, Tesla needs to find a new growth engine capable of justifying its exceptional stock market valuation.

Optimus could become precisely that new strategic narrative.

Some investors are even beginning to believe that Tesla could one day become more of a robotics and AI company than a traditional automaker.

The idea still seems radical. Yet Elon Musk himself already appears to be preparing this transition.

Tesla’s real advantage: physical artificial intelligence

Unlike many robotics companies, Tesla already has a massive advantage: its accumulated expertise in real-time AI and computer vision.

Tesla cars are already, in a way, autonomous robots on wheels. They use:

Cameras Neural ; networks Proprietary; chips Perception ; systemsMassive ; learning models

Tesla is now applying this same logic to Optimus.

The humanoid robot then becomes a physical extension of the artificial intelligence developed for autonomous driving.

And this is probably the heart of the project.

Tesla is not simply trying to build a spectacular robot. The company is trying to build an AI platform capable of interacting with the physical world.

In this vision, AI no longer remains confined to a screen or a chatbot. It becomes mobile, autonomous, and capable of acting in the real world.

The global battle for humanoid robots has already begun

Tesla, however, is not alone in this market.

China is now investing massively in humanoid robots. Beijing now considers this technology a national strategic sector.

Companies such as Unitree, UBTech, Fourier Intelligence, and Xiaomi are accelerating their developments. Demonstrations are multiplying. Public and private investments are exploding.

And China has several major advantages:

• Industrial power
• Battery expertise
• Electronics
• Components
• Supply chains
• Large-scale production capacity

In response, Tesla is trying to capitalize on its software lead and its unique ability to industrialize complex products quickly.

Because this is probably the group’s other major strength: Tesla knows how to produce at scale.

And if Optimus one day becomes economically viable, Tesla could rapidly accelerate global production.

But the bet remains extremely risky

Despite the growing enthusiasm around humanoid robots, the technological reality remains extremely complex. Designing a robot capable of moving autonomously in the real world still requires solving many major challenges related to balance, mobility, object manipulation, energy autonomy, safety, environmental understanding, and human interaction.

Today, no market player has yet demonstrated a truly autonomous, reliable, and profitable humanoid robot at large scale. The sector therefore remains largely speculative, which fuels many debates around Tesla’s valuation.

A significant part of the group’s stock market value now rests on future markets that are still emerging, such as humanoid robotics, full autonomous driving, physical AI, and generalized automation.

In other words, Tesla is no longer valued as a simple automaker, but as a technology player betting on the industries of the future.

Tesla is no longer valued
like a traditional
automaker.

Meanwhile, SpaceX is increasingly fascinating Wall Street

While Tesla has historically captured most of the market’s attention, another Elon Musk company is increasingly attracting investors: SpaceX.

Long inaccessible to the general public, SpaceX is now considered one of the most strategic private companies in the world.

And many analysts believe that a future IPO could become one of the most important financial events of the decade.

Unlike many space companies, SpaceX already generates:

• Recurring revenue
• Government contracts
• Commercial launches
• Above all, a global telecom business through Starlink

The group now largely dominates the Western space market.

And most importantly, SpaceX has technological barriers that are extremely difficult to replicate.

Could a SpaceX IPO weaken Tesla?

This is now a question some funds are beginning to take seriously.

Today, some investors buy Tesla to gain indirect exposure to Elon Musk and his ability to innovate.

But if SpaceX went public, part of that capital could naturally shift.

Why?

Because many now believe that SpaceX has:
A stronger technological lead, less competition, strategic revenues and enormous geopolitical potential

In electric vehicles, Tesla now faces extremely aggressive global competition.

In space, SpaceX still maintains an impressive level of dominance.

Some investors could therefore choose between the two companies. And this could gradually change how Tesla is perceived on financial markets.

Is Elon Musk trying to build the technological infrastructure of the future?

Ultimately, Tesla, Optimus, Starlink, and SpaceX now seem to be part of a much broader vision.

Elon Musk now appears to want to connect several technology sectors within a single global vision combining artificial intelligence, robotics, energy, automation, space, and global networks.

In this approach, Tesla cars gradually become autonomous robots capable of interacting with their environment, while Optimus could represent a future physical workforce for factories, logistics, or services.

At the same time, Starlink is positioning itself as a global communications infrastructure, while SpaceX develops the space capabilities of the system. Few entrepreneurs in history have attempted such vast technological integration.

In this context, Tesla’s bet on Optimus goes far beyond the simple development of a humanoid robot. The company seems to be gradually preparing its transformation toward a model much more centered on artificial intelligence, software, robotics, and global automation.

In the coming years, Tesla could even gradually reduce its dependence on automobiles and invest more heavily in humanoids and physical AI.

But this bet remains extremely ambitious and risky.

Because despite impressive demonstrations, humanoid robots are still far from mass adoption at large scale.

Meanwhile, SpaceX increasingly appears to be another key pillar of the Musk empire.

And a future IPO could divert some of the attention and capital currently focused on Tesla.

One thing, however, seems clear:
Elon Musk is no longer simply building cars.
He is now trying to redefine the technological economy of the future.

Author : Christophe Carl Louis
Article assisted by an IA

FAQ – Tesla, Optimus, and SpaceX

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As humanoid robotics attracts increasing attention worldwide, a growing number of startups are exploring new real-world applications for these machines. While many companies aim to build general-purpose humanoids capable of performing multiple tasks, TeknTrash Robotics is taking a different approach.

The company focuses on a very specific mission: automating waste handling through humanoid robots.

Robot Magazine spoke with Al Costa, entrepreneur and robotics advocate, about the company’s vision, the evolution of humanoid systems, and why specialization could be the key to making robots truly useful in everyday environments.

Introducing TeknTrash

Robot Magazine: To start, could you briefly explain what TeknTrash does, the problem your company addresses, and the vision that drives your work in robotics and automation?

Al Costa:
TeknTrash was created based on a simple observation: waste handling  both in industrial environments and in homes  is dangerous, unsanitary and unhealthy. It is a task that ideally humans should not have to perform.

To solve this problem, we developed ALPHA, the Automated Litter Processing Humanoid Assistant. ALPHA is a humanoid robot specifically designed to handle waste in many environments.

Our vision differs from many robotics companies currently developing humanoids. The idea of creating general-purpose humanoids capable of performing any task is, in my opinion, unrealistic.

When a company hires someone, it does not expect that person to code software, manage finances, serve coffee and answer customer calls simultaneously. Each job requires a different set of skills.

Biology teaches us the same lesson: specialization matters. Muscles designed for strength cannot perform precision tasks efficiently, and precision muscles cannot deliver high force.

For that reason, TeknTrash focuses entirely on waste handling. This specialization is the foundation of our strategy.

“Robotics should follow the same logic as human work: specialization creates efficiency.”
Al Costa, CEO of TeknTrash Robotics

Humanoid robotics and real-world applications

Robot Magazine: Humanoid robots are attracting strong attention across the robotics industry. How do you see these systems evolving from experimental platforms into real-world solutions?

Al Costa:
My background combines biology and computer engineering, which allows me to approach robotics from both scientific and technological perspectives.

Two years ago, I suggested to an investor that robots could be used during concerts as part of the entertainment experience. At the time, he dismissed the idea, arguing that robots would “sell themselves”.

But recently we saw a major pop concert in China where four humanoid robots danced alongside the singer. The audience loved it.

This example illustrates a broader point: China is currently far ahead in experimenting with real-world uses of robotics. If Western companies want to remain competitive, we need to closely observe what is happening there.

At TeknTrash we opened an office in Suzhou, and I may personally relocate to China in the future.

“China is moving extremely fast in robotics
adoption. Watching what happens there is essential.”
Al Costa

Systems thinking in robotics

Robot Magazine: Modern robotics increasingly relies on integrated systems combining AI, sensors and connectivity. How does TeknTrash approach this challenge?

Al Costa:
One of the biggest limitations for robotics today is computing power.

Human brains are made of carbon atoms. Carbon has the same four chemical bonds as silicon which is used in computer chips but carbon atoms are much smaller. This allows biological brains to pack incredible computing capacity into a very small space.

As a result, the human brain still far surpasses any computer we can currently build.

At the same time, semiconductor manufacturing is approaching atomic limits. Chips cannot keep shrinking indefinitely.

Because of this, robotics will increasingly rely on cloud computing.

Many advanced robotic functions will not run directly on the robot itself but on remote servers performing heavy computations.

This means robots must be connected continuously to powerful computing infrastructure.

TeknTrash is part of the One6G Association, exploring future connectivity technologies. Our architecture has also been recognized by Google Cloud as an example of cloud-based robotics.

“The future of robotics will rely heavily
on cloud intelligence rather than onboard
computing.”

Automation, intelligence and the future of work

Robot Magazine: Beyond productivity gains, how will intelligent automation reshape industries and society?

Al Costa:
Recently a well-known billionaire suggested that robots could eliminate the need for human work within five years.

That reminded me of the film WALL-E, where robots perform every task for humans and society becomes completely dependent on machines.

While that scenario may sound extreme, technological progress is clearly accelerating.

The futurist Ray Kurzweil described this phenomenon with the concept of the technological singularity  a point where technological evolution becomes so rapid that predicting the future becomes extremely difficult.

Whether or not we reach that point soon, intelligent automation will undoubtedly transform many industries in the coming decades.

Leadership and the future of robotics

Robot Magazine: What mindset shift is required to accelerate the adoption of humanoid robots?

Al Costa:
Technological pessimism has always existed.

When the telephone was invented, many people believed it was unnecessary because the telegraph already worked perfectly.

Innovation often faces resistance because people cannot imagine how new technologies will change everyday life.

Henry Ford famously said that if he had asked customers what they wanted, they would have answered: “a faster horse”.

Today many societies face labor shortages due to demographic changes. In Japan, for example, more adult diapers are sold than baby diapers.

This shows that robots will increasingly be needed to supplement human labor.

Our responsibility as technologists is to develop tools that improve society, even when people initially struggle to imagine their value.

About Al Costa

Al Costa is CEO of TeknTrash Robotics, a company focused on developing humanoid robots dedicated to waste handling in industrial and residential environments.

A serial entrepreneur, he has founded companies in the United States, the United Kingdom, Spain, China and Brazil. His first startup was acquired by a company listed on NASDAQ.

He is also the author of five books, including a science-fiction novel, and previously taught Big Data and Machine Learning at a university in Spain.

Having grown up in several countries as the son of a diplomat, he is also the founder of an NGO dedicated to protecting children in war zones.

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In this emerging model, companies no longer purchase humanoid robots. Instead, they simply subscribe to robotic labor capacity, much like they already subscribe to cloud services or software today.

With the arrival of humanoid robots developed by companies such as Tesla, Figure AI, Agility Robotics, and Apptronik, some industry players are already considering subscription-based business models.

If this trend continues, humanoid robots could profoundly transform the labor economy and create a market estimated at more than $100 billion in the coming decades.

What is Humanoid-as-a-Service?

Humanoid-as-a-Service (HaaS) is a model in which a humanoid robot is provided as a service rather than sold as a product.

Instead of purchasing a robot for several hundred thousand euros, a company could simply pay for:

• A monthly subscription

• An hourly rate

• A cost per completed task

In this model, the provider manages:

• The robot itself

• Software updates

• Maintenance

• Integration

• Algorithm improvements

The client company only pays for the actual use of the robot.

This approach transforms a heavy industrial investment into an operational expense, making the adoption of robotics significantly easier.

After SaaS and RaaS, Humanoid-as-a-Service
could represent the next economic
evolution of robotics.

Why Humanoid Robots Fit the “As-a-Service” Model

Humanoid robots have a unique characteristic: they are designed to operate in environments built for humans.

Unlike traditional industrial robots, which often require specialized infrastructure, humanoids can theoretically:

• Walk through a warehouse

• Handle objects

• Use tools

• Transport packages

• Work alongside human workers

This flexibility makes humanoid robots particularly compatible with on-demand service models.

For example, a company could rent a humanoid robot to:

• Handle a logistics activity peak

• Temporarily compensate for a labor shortage

• Automate repetitive tasks

Companies Exploring This Model

Several companies developing humanoid robots could adopt a Humanoid-as-a-Service model.

Tesla

Tesla is developing the humanoid robot Optimus, designed to work in factories and warehouses.

Elon Musk regularly mentions the possibility of deploying these robots at large scale in industry.

A subscription-based model could accelerate their adoption.

Figure AI

The startup Figure AI is developing the humanoid robot Figure 01, with the goal of deploying these machines in industrial environments.

The company has attracted strong investor attention after raising hundreds of millions of dollars.

Its business model could evolve toward on-demand robotics services.

Agility Robotics

Agility Robotics develops the humanoid robot Digit, designed for logistics and material handling.

Digit is already being tested in some warehouses to:

• Transport packages

• Automate certain operations

Apptronik

Apptronik develops the humanoid robot Apollo, designed for industrial applications.

The goal is to create a robot capable of assisting workers with physical tasks.

Industries That Could Adopt HaaS

Several sectors could quickly benefit from the Humanoid-as-a-Service model.

Logistics

Warehouses represent an ideal testing ground for humanoid robots.

They could:

• Load and unload packages

• Move goods

• Prepare orders

• Assist human operators

Manufacturing

In factories, humanoid robots could handle repetitive physical tasks.

They could also be used to operate in difficult or hazardous areas.

Services

In the longer term, humanoid robots could appear in:

• Hotels

• Airports

• Hospitals

• Shopping malls

They could assist human teams in logistics operations or customer support tasks.

A Potential Market Worth Over $100 Billion

Analysts believe humanoid robots could become one of the largest markets in robotics.

Several factors support this growth:

• Labor shortages in many countries

• Increasing productivity pressure

• Advances in artificial intelligence

• Gradual reductions in component costs

Some projections estimate a market exceeding $100 billion by 2040.

If the Humanoid-as-a-Service model becomes widespread, it could significantly accelerate this growth.

Logistics already represents an
ideal experimentation environment
for humanoid robots.

Toward a Robotic Labor Economy

The Humanoid-as-a-Service model could transform how companies access labor.

Instead of hiring employees for certain repetitive tasks, companies could simply subscribe to robotic workforce capacity.

We could eventually see:

• Humanoid robots rented by the hour

• Robots billed per task

• Robot fleets managed through cloud platforms

This model fits within a broader shift toward an economy of automated services.

Challenges to Overcome

Despite its potential, the Humanoid-as-a-Service model still faces several challenges.

Robot Costs

Humanoid robots are still expensive to manufacture.

Reliability

To operate in industrial environments, these robots must be extremely reliable.

Energy Autonomy

Battery technology remains a limiting factor for extended operation.

Humanoid robots could represent the next major revolution in industrial robotics. By combining artificial intelligence, advanced robotics, and subscription-based economic models, the concept of Humanoid-as-a-Service could transform how companies access automation.

Instead of purchasing robots, companies may soon subscribe to robotic labor.

If this vision becomes reality, humanoid robots could create a new industry worth more than $100 billion and mark the beginning of a new automated labor economy.

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The Rise of Intelligent Industrial Robotics

Since the 2010s, industrial automation has experienced exponential growth, with articulated robots capable of welding, assembling, or painting at high speed in controlled environments. However, these systems remain limited by their rigidity: any change to the production line often requires complete reengineering. Humanoid robots, in contrast, introduce unprecedented flexibility.

Equipped with advanced sensors, precise articulated arms, and 3D vision systems, these robots can perform complex tasks in semi-structured environments. Giants like Toyota, Siemens, ABB, and Fanuc are now investing in hybrid solutions that combine traditional industrial robots with collaborative humanoids. This approach allows for the automation of operations previously reserved for skilled human operators, while retaining the ability to respond to unexpected variations.

Artificial intelligence plays a central role in this transformation. Humanoid robots can learn work sequences, detect anomalies in real-time, and adjust their actions to maximize efficiency. AI algorithms also enable continuous optimization of production lines by analyzing millions of data points to reduce downtime and improve product quality.

Humanoid robots are no
longer just experimental
tools.

Humanoids and Logistics: A Revolution Underway

Beyond production lines, logistics is one of the sectors where humanoid robots demonstrate their potential. In warehouses and distribution centers, robots like Agility Robotics’ Digit or Tesla Robotics prototypes can transport packages, sort goods, and collaborate with human workers. Their ability to handle objects of various sizes and shapes, navigate narrow aisles, and adapt to dynamic conditions reduces the need to reorganize existing infrastructures.

Integrating humanoid robots in logistics also enables real-time data collection. They can monitor inventory, detect packaging anomalies, and contribute to full product traceability. For e-commerce and retail giants, this combination of autonomy, precision, and data collection is a major strategic factor to meet growing demand and increasingly tight delivery timelines.

Massive Investments for Strategic Returns

Industrial giants are not just deploying humanoid robots they are investing billions in research and development to perfect these technologies. According to recent McKinsey & Company data, global investments in advanced robotics and AI for industry are expected to exceed $30 billion by 2026. These investments cover hardware, software, and human operator training to work effectively with these robots.

These investments are driven by several factors:

• Skilled labor shortage: In many sectors, recruiting experienced operators has become a major challenge. Humanoid robots help compensate for this deficit and secure production.

• Operational flexibility: Unlike traditional robots, humanoids can be quickly reprogrammed for new tasks or products, reducing reengineering costs.

• Competitiveness and innovation: Companies that effectively integrate humanoid robots gain speed, precision, and reliability, creating a strategic advantage over competitors.

Humanoids and Industrial Maintenance: A Winning Duo

Predictive and assisted maintenance using humanoid robots is another area where industrial giants are betting big. In complex factories, humanoids can inspect machines, detect anomalies, perform simple repairs, and collaborate with human technicians on more complex interventions.

With advanced sensors and onboard AI systems, robots can identify abnormal vibrations, overheating, or deformations—often before these issues cause production downtime. This reduces costs associated with breakdowns and enhances worker safety. Some companies are also experimenting with humanoids capable of handling specialized tools or assembling delicate components—tasks previously requiring significant human expertise.

Ethical and Regulatory Challenges

The widespread adoption of humanoid robots raises significant ethical and legal questions. Responsibility in the event of an incident, protection of data collected by robots, and impacts on human employment are central to the debate.

Governments and international organizations are beginning to establish regulatory frameworks. The European Union has launched initiatives to regulate collaborative and humanoid robots, while in the U.S. and Asia, sector-specific guidelines are emerging to ensure safety, compliance, and data protection. Companies must not only comply with these standards but also build trust among employees and customers to ensure sustainable adoption.

Predictive maintenance and assisted
interventions become safer and
more efficient.

Toward Human-Machine Collaboration

The success of humanoid robots in industry depends not only on technology but also on human acceptance. Industry giants emphasize ergonomic design, intuitive interaction, and transparency in robot actions. Specific training programs and collaboration protocols are implemented to ensure smooth integration into mixed teams.

This human-machine collaboration paves the way for a new work organization, where robots handle repetitive or hazardous tasks, and humans focus on supervision, decision-making, and solving complex problems. The benefits are twofold: increased safety and optimized productivity.

In 2026, industrial giants are heavily investing in humanoid robots to address major strategic challenges: flexibility, competitiveness, safety, and innovation. This transition marks a decisive step in the history of industrial robotics, where the boundary between humans and machines is becoming increasingly collaborative.

While widespread adoption of humanoid robots remains a technological, economic, and social challenge, current trends suggest a future where factories, warehouses, and maintenance centers may operate through effective symbiosis between human operators and humanoid robots. Companies that anticipate this revolution will gain a major competitive advantage, while humanoid robots will evolve from technological curiosities into indispensable strategic partners.

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Generative AI and Humanoid Robots: A Strategic Duo

At the heart of this evolution is the rise of generative and adaptive artificial intelligences. Humanoid robots are no longer simply machines programmed to perform mechanical tasks: they are becoming capable of understanding and interacting with complex environments, making real-time decisions, and even learning from their experiences.

Companies like Boston Dynamics, Hanson Robotics, and Tesla Robotics are pushing the limits of embedded AI. Integrating sophisticated language models enables robots to interpret complex instructions, communicate with humans, and perform multi-step tasks without constant supervision. This autonomous learning capability is crucial for deployment in environments where unpredictability is the norm, whether in a logistics warehouse, a production factory, or an assisted living home.

Another key factor is the fusion of computer vision models and advanced tactile perception. Humanoid robots equipped with high-resolution cameras and haptic sensors can now navigate unstructured environments, identify objects, and handle tools with near-human precision. In 2026, these capabilities will be robust enough to move beyond laboratories and integrate into production lines or service operations.

Humanoid robots are no longer
mere machines: they learn, adapt,
and interact.

Miniaturization and Lightweight Robotics: Lowering the Hardware Barrier

Alongside software advances, the hardware of humanoid robots is undergoing a revolution. Electric motors are becoming more compact and powerful, batteries offer longer autonomy, and composite materials reduce weight while increasing strength. These improvements allow robots to move more fluidly, withstand physical stress, and operate longer without recharging.

Miniaturization of electronic components and actuators also provides unprecedented modularity. Humanoid robots can now be designed for specific applications, whether home care, logistics support, or industrial monitoring. This flexibility makes investments more attractive to companies, as it allows the robot to be adapted to different scenarios without fully reinventing the machine.

Humanoid Robots and Industry: Towards smart production

Industry is one of the sectors most likely to benefit from this new generation of humanoid robots. Unlike traditional industrial robots, often confined to repetitive tasks in enclosed environments, humanoids can work alongside human operators, collaborate in mixed lines, and adapt to changing conditions.

In warehouses and logistics, for example, humanoid robots can handle sorting, transporting, and storing packages in cluttered spaces. Their anthropomorphic form and ability to manipulate varied objects reduce the need to redesign existing infrastructure a cost often prohibitive in conventional industrial automation.

Furthermore, humanoid robots can serve as real-time data collection points. With multiple sensors, they can monitor product quality, detect anomalies, and provide valuable insights to AI systems to optimize production. This approach fits perfectly with the Industry 4.0 philosophy, where system flexibility and intelligence are key competitiveness factors.

Social and Medical applications: A growing market

Beyond industry, humanoid robots are finding roles in social and medical services. Aging populations and shortages of qualified healthcare personnel are powerful drivers for the development of robots capable of assisting patients and dependent individuals.

Humanoid robots can perform monitoring tasks, deliver medications, or even provide emotional support. For instance, prototypes of robotic companions can already detect signs of distress in elderly people and notify caregivers when needed. By 2026, the combination of enhanced physical capabilities and social AI will enable more natural and less intimidating interactions, paving the way for broader adoption in homes and healthcare facilities.

Ethical and Regulatory Challenges

The widespread adoption of humanoid robots will not happen without challenges. Questions of safety, responsibility, and ethics are front and center. Who is liable if a robot causes harm? How can we ensure that data collected by robots does not violate individuals’ privacy?

International organizations are beginning to develop safety standards and ethical guidelines to regulate the use of humanoid robots. The European Union, for example, is investing in certification programs to ensure that robots meet minimum safety and data protection standards. In the United States, regulation remains fragmented but is advancing in healthcare and personal assistance domains.

End-user trust will be a decisive factor in commercial success. Humanoid robots must not only be safe and reliable but also socially acceptable. Design, communication ability, and transparency in machine operation are key elements to overcome initial public skepticism.

Safety, responsibility, and transparency
are the keys to democratizing
robots.

2026: An unprecedented Technological convergence

If 2026 is expected to be the pivotal year for humanoid robots, it is primarily due to a unique convergence of factors:

• Advanced artificial intelligence: autonomous decision-making, natural language understanding, adaptive learning.

• Enhanced perception and manipulation: next-generation visual and haptic sensors.

• Optimized materials and motors: lightweight, durable, extended autonomy.

• Growing social acceptance: more human-like design, integration into existing environments.

• Regulatory and ethical ecosystems: safety standards, data protection, legal accountability.

This combination creates a context in which humanoid robots can move from being technological curiosities to strategic tools across multiple sectors.

In 2026, humanoid robots could finally move beyond prototypes and spectacular demonstrations to become essential players in industry, services, and even daily life. This transition will not be automatic or uniform worldwide, but recent advances suggest a gradual and strategic adoption. Companies and institutions that anticipate this wave will gain a major competitive advantage, while researchers and engineers will continue to push the limits of AI and anthropomorphic robotics.

If 2026 is the pivotal year, it may well mark the beginning of an era where humanoid robots are no longer mere machines but active partners in transforming our societies.

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The global race in intelligent robotics has reached a new milestone. Google DeepMind has announced the opening of applications for its Accelerator: Robotics, an intensive three-month program designed to support European startups developing the next generation of intelligent robots.

At a time when the convergence of artificial intelligence and physical systems is redefining industry, this accelerator positions itself as one of the most strategic programs for European founders in the field.

Accelerating the Era of Embodied AI

Over the past two years, robotics has undergone a major transformation driven by the rise of generative AI applied to the physical world, often referred to as Embodied AI. Unlike purely software-based models, these systems enable robots to understand, reason, and act within real-world environments.

With this program, Google DeepMind is clearly targeting companies working on:

• Advanced industrial automation

• Mobile robotics and autonomous navigation

• Humanoid robots

• Intelligent manipulation

• Robotic logistics

• Next-generation autonomous systems

The goal is simple: to bring robotic innovations from the lab to market faster.

Embodied AI transforms robots
into systems capable of understanding
and acting in the real world.

Direct Access to Google’s AI Technologies

The program’s main advantage lies in privileged access to technologies developed by Google DeepMind, including:

• AI models and robotic reasoning tools from the Gemini family

• Cloud and compute infrastructure tailored for robotic workloads

• Technical guidance from DeepMind researchers and engineers

• Product and go-to-market mentorship to accelerate commercialization

For many startups, access to this level of infrastructure would normally require millions of euros in investment.

A European Response to Global Competition

This initiative comes amid intense technological competition between the United States, China, and Europe in advanced robotics.

While players like:

• Boston Dynamics

• Figure AI

• Agility Robotics

are accelerating the development of robots capable of operating in human environments, Europe seeks to strengthen its startup ecosystem to compete on a global scale.

The DeepMind accelerator could thus play a key role in preventing a European technological gap.

From Research to Industrialization

Historically, one of European robotics’ major challenges has been scaling innovations to industrial levels. Many breakthroughs emerge from universities or research centers but struggle to achieve rapid commercial adoption.

The program therefore places strong emphasis on:

• Product validation

• Real industrial use cases

• Commercial strategy

• Access to international markets

This focus reflects a major evolution: robotics is now entering a phase of mass industrialization, driven by AI.

Founders who master
AI and hardware will shape
the next decade.

An Opportunity for Robotics & Physical AI Founders

For European entrepreneurs, this initiative represents far more than a standard acceleration program. It offers:

• Immediate credibility with investors

• Direct access to a global ecosystem

• Significant technological acceleration

• Strategic exposure to industrial partners

In a market where funding is becoming more selective, the support of a player like Google DeepMind can serve as a true growth catalyst.

Towards a New Generation of Intelligent Robots

The announcement confirms a fundamental trend observed by Robot-Magazine.fr: robotics is entering a new phase dominated by general-purpose AI applied to physical machines.

After the era of programmed automation and collaborative robotics, the next decade will belong to robots capable of learning and adapting in real time.

European startups now have a strategic window to establish themselves in this revolution.

Applications are open now:
https://goo.gle/robotics

For founders building the next generation of autonomous robots, the message is clear: AI and robotics are now one, and the global race has begun.

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In 2026, the answer is neither a triumphant yes nor a categorical no. It lies in an intermediate zone, where technological progress, economic constraints, and operational realities gradually reshape the role of these machines in the workplace.

Why the Question Arises Today

Until recently, humanoid robots were primarily research projects or technology showcases. Their cost, complexity, and lack of reliability confined them to laboratories or demonstration setups.

What has changed is not just robotics itself, but the convergence of several breakthroughs: rapid progress in artificial intelligence, lower sensor costs, better batteries, increased onboard computing power, and growing pressure on the labor market.

Labor shortages, an aging population, heightened safety requirements: in this context, certain human tasks are becoming hard to fill or too costly in the long run. Humanoid robots appear as a potential solution not to replace humans entirely, but to take over targeted functions.

Humanoid robots don’t
replace humans they
reshape work.

What Humanoid Robots Can Actually Do Today

Modern humanoid robots have crossed several major technical thresholds. They can walk stably, manipulate simple objects, perceive their environment, and perform relatively complex task sequences.

Players like Tesla with Optimus, Boston Dynamics, and several Asian manufacturers have demonstrated credible capabilities in semi-structured environments.

Concretely, humanoids today are capable of:

• Carrying light to medium loads

• Performing repetitive manipulations

• Moving through spaces designed for humans

• Interacting safely with operators

• Following simple procedures with a degree of autonomy

However, they remain limited whenever tasks require fine dexterity, deep contextual understanding, or creative adaptation.

Which Human Tasks Are Actually Concerned

The question is not whether humanoid robots can replace “humans,” but which specific tasks they can perform reliably, cost-effectively, and safely.

The first credible use cases involve tasks with low cognitive value but high physical or organizational constraints:

• Light and repetitive handling

• Internal logistics in factories or warehouses

• Industrial site inspection

• Monitoring sensitive areas

• Assistance in hazardous or constrained environments

In these contexts, humanoid robots are not chosen for their intelligence, but for compatibility with existing human environments without major infrastructure modifications.

Humanoids as a Complement, Not a Replacement

Contrary to common fears, humanoid robots do not replace entire professions. They replace task segments often the most tedious, repetitive, or unattractive.

In industry, they complement:

• Traditional industrial robots, which are too rigid

• Cobots, sometimes limited in mobility

• Human operators, facing fatigue or physical risks

This hybrid model increases the overall capacity of the production system without eliminating human value. The operator becomes a supervisor, coordinator, or expert, rather than a mere executor.

Real Technical Barriers

Despite progress, humanoid robots still face significant limits. Energy autonomy is restricted, maintenance is complex, and long-term reliability is not yet proven at scale.

Safety remains a central concern. Due to their size and power, humanoid robots pose specific risks in case of malfunction. Certification, regulatory compliance, and team acceptance are still open challenges.

Finally, onboard AI, though capable, remains fragile in unforeseen situations. Robots excel in defined frameworks but still struggle to handle the ambiguity of the real world with human-like flexibility.

The future of work will not
be robotic or human it will
be hybrid.

More of an Economic Challenge Than a Technological One

The maturity of humanoid robots depends as much on economics as on technology. To replace a human task, a robot must be:

• Cost-effective over its entire life cycle

• Easy to deploy and maintain

• Versatile enough to justify its cost

• Socially and legally acceptable

Today, only very specific environments meet these conditions. But the trajectory is clear: as costs fall and reliability increases, the range of replaceable tasks will expand.

A Gradual Transformation of Work

The arrival of humanoid robots reveals a profound transformation of the concept of work. The debate is no longer only about employment, but about the allocation of roles between humans and machines.

Robots handle standardized physical execution. Humans retain supervision, decision-making, creativity, and accountability. This complementarity requires evolving skills, training, and organizational structures.

The challenge is therefore not only technological, but also social and managerial.

Ready to Replace Tasks, Not Humans

Humanoid robots are not ready to replace humans entirely. However, they are already capable of taking over specific human tasks, in targeted environments and under strict conditions.

This gradual shift marks a new stage in industrial automation. It is no longer about isolated machines, but intelligent physical agents integrated into complex production systems.

The real question for industry is therefore not whether humanoid robots will replace humans, but how to integrate them intelligently to enhance performance, safety, and organizational resilience.

The future of work will be neither entirely human nor entirely robotic. It will be hybrid, adaptive, and profoundly transformed by these new forms of human-machine collaboration.

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To understand the genesis of RobotShop, you need to go back to my past as a combat engineer in the Canadian Army. During a mission in the former Yugoslavia, I faced the terrifying reality of landmines. Enemy technology was evolving rapidly metal, light, vibration, pressure, and pressure-release sensors while we were still often clearing mines lying on the ground with just a bayonet. I remember thinking: “I need to get out of here before I lose my life.”

After leaving the army, I pursued studies in robotics engineering, keeping in mind the idea of creating swarms of small “kamikaze” robots for humanitarian demining. To learn and become an expert, I started building robots in my apartment.

My first prototype, in the early 2000s, wasn’t a deminer it was a “Cat Hunter”! Imagine a chassis made from a tackle box, BBQ wheels, a thermal sensor salvaged from a garage light, glued onto a stepper motor recovered from a printer that served as the tracking head. I even rigged a tactile bumper using a copper tube and a piezoelectric component taken from an old speaker to detect obstacles, all controlled by a microcontroller programmed in BASIC. The robot worked so well it relentlessly chased my cat I had to deactivate it to preserve the animal’s sanity (laughs)!

But this “Maker” experience, building robots constantly, revealed a real problem: sourcing parts was a logistical nightmare. Every component had to be ordered from different places around the world. I realized that for robotics to advance, creators needed a centralized source. RobotShop was born from this frustration: creating a single platform to make it easier for enthusiasts and engineers to build useful robots for the future.

How has RobotShop’s mission evolved as the robotics market matured, from education to industry?

At first, the non-industrial market was mainly education, research, and Makers, with a few domestic applications like robot vacuum cleaners. We liked to call ourselves “the Amazon of robotics,” a simple way to explain what we did. Our unofficial slogan was “robotics at your service,” meaning we wanted to bring robotics into people’s lives in a concrete and useful way.

Today, the sector has matured, and we’ve evolved with it. We are no longer just a robotics store; we’ve become a global platform offering robotic solutions. Our new slogan is: “Everything Robotics, infinite possibilities”.

We began offering commercial and professional solutions, supported by a growing network of integrators. From robot kits to humanoids, we offer it all, aiming to accelerate and expand our range. From discovering the right robotic solution to financing, deployment, support, maintenance, and purchase or rental that’s what RobotShop is becoming.

We also opened our first showroom in Mirabel, Canada, which is essentially a living lab where customers can visit us. We plan to replicate this physical presence extensively, not only in Canada but internationally.

Our ambition is to build a global ecosystem where any robotic project can come to life through RobotShop.

With your unique perspective, what does the market still underestimate most in robotics: technology, applications, or real adoption?

All of the above (laughs). Take, for example, how humanoid robots will arrive in real-world applications faster than people think. There is still a lot of skepticism, which I understand. People see videos of robots dancing or doing flips and ask: “Okay, but what’s the practical use?”

What is less visible are the exponential forces working behind the scenes. I’m talking about major advances in three areas that reinforce each other: artificial intelligence, GPU power, and mechatronics (the physical dexterity of robots). AI allows robots to understand, adapt, and reason. Next-gen GPUs enable ultra-fast real-time computation, even locally. And physically, robots are becoming more stable, fluid, and capable of manipulating their environment precisely.

The combination of these three factors is a complete game-changer.

Few people also realize that major automotive manufacturers are already involved. Several have signed agreements with humanoid robot companies to integrate them, in the short term, into their assembly lines. These same partnerships, backed by industrial power, will enable mass production. We are no longer talking about lab prototypes; we’re talking about general-purpose humanoid platforms capable of performing a wide range of tasks just like a human, and in some cases, better.

Security and data privacy issues? They will be addressed in parallel. There will be rapid iterations, updates, and standards emerging, as always with disruptive technologies.

The result is that when these robots are “good enough” to replace certain human tasks at scale, they will be produced, delivered, and deployed massively and very quickly. It won’t be a slow, gradual change; it will be a wave.

As with all major technological breakthroughs, we radically underestimate the adoption speed once everything aligns.

If you had to summarize in one sentence the mission you still pursue today with RobotShop, what would it be?

“Together, fostering a world full of robots that positively impacts our lives.”

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