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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While Western and Japanese robotics programs often prioritize research excellence or long-term breakthroughs, Chinese industrial players are approaching humanoid robots with a distinctly different mindset: build fast, deploy early, iterate in production environments. The result is a rapid transition from experimental prototypes to real-world industrial trials.

This shift does not mean humanoid robots are suddenly replacing human workers at scale. It does mean they are crossing a critical threshold from concept to industrial asset.

A Pragmatic View of the Humanoid Robot

In China, humanoid robots are not framed as futuristic replicas of humans. They are treated as general-purpose industrial platforms designed to operate in environments built for people.

Factories, warehouses, power plants, logistics hubs, and public infrastructure were designed around human dimensions stairs, doors, workbenches, corridors. The humanoid form factor is therefore seen not as an aesthetic choice, but as a practical solution to avoid costly infrastructure redesign.

Chinese manufacturers focus on what humanoid robots can do today: basic manipulation, mobility, inspection, transport, and assistance in semi-structured environments. The emphasis is on usefulness, not perfection.

In robotics, the real breakthrough
is not intelligence it’s
industrialization.

An Industrial Ecosystem Built for Speed

One of China’s strongest advantages lies in its industrial ecosystem. Unlike fragmented supply chains elsewhere, China benefits from a highly integrated hardware manufacturing base.

Key components motors, reducers, batteries, sensors, cameras, embedded computing boards, power electronics are produced domestically or regionally, often within the same industrial clusters. This proximity dramatically reduces development cycles.

When a design flaw appears, components can be revised, tested, and reintegrated in weeks rather than months. Prototyping and pre-series production move quickly, allowing manufacturers to reach industrial readiness far sooner than many global competitors.

Designing Humanoids for Manufacturability

Chinese humanoid robots increasingly reflect a “design-for-manufacturing” philosophy. Rather than pursuing complex, bespoke mechanisms, manufacturers prioritize:

• Modular limb architectures

• Standardized joint actuators

• Simplified mechanical transmissions

• Repeatable assembly processes

• Scalable bill-of-materials structures

This approach mirrors the playbook used in China’s electric vehicle sector: industrialize first, refine later. Humanoid robots are no longer treated as one-off machines, but as platform products capable of evolving through generations.

The goal is not to create the most advanced humanoid robot on paper, but the one that can be built, serviced, and deployed at scale.

AI as an Enabler, Not a Marketing Tool

Artificial intelligence plays a central role but in a restrained and functional way. Rather than chasing artificial general intelligence, Chinese developers focus on task-oriented autonomy.

Key areas of AI deployment include:

• Visual perception for object recognition and localization

• Learning-by-demonstration for industrial gestures

• Balance and motion planning in dynamic environments

• Basic decision-making under uncertainty

This pragmatic use of AI enables humanoid robots to operate effectively without requiring excessive computational overhead or unrealistic performance expectations. Reliability matters more than sophistication.

As a result, these systems may appear less impressive in demos but they perform more consistently in real industrial conditions.

Early Industrial Use Cases Are Already Emerging

Several Chinese manufacturers are already testing humanoid robots in real operational settings. These deployments remain limited in scope but are significant in intent.

Current use cases include:

• Internal logistics within large factories

• Transport of light components and containers

• Inspection of equipment and facilities

• Repetitive handling tasks in controlled zones

• Operations during night shifts or low-staffed periods

In most cases, humanoid robots are positioned as support systems, not replacements. They complement existing automation and human labor, filling gaps where flexibility is required.

Government Support Focused on Deployment, Not Just R&D

China’s public sector plays a critical but often misunderstood role. Rather than concentrating solely on research funding, government policies emphasize industrial validation and market creation.

Pilot zones, test facilities, procurement programs, and public-private partnerships provide real environments where humanoid robots can be evaluated under operational constraints. This reduces risk for manufacturers and accelerates learning cycles.

The domestic market serves as a proving ground before international expansion allowing Chinese firms to refine products at scale before competing globally.

How China Differs from the US, Japan, and Europe

The Chinese approach contrasts sharply with other major robotics regions.

The United States excels in AI software, simulation, and high-level robotics intelligence but often struggles with large-scale hardware industrialization.

Japan remains a global leader in precision mechanics and reliability, yet tends to move cautiously when it comes to radically new form factors.

Europe emphasizes safety, regulation, and industrial integration, which can slow down early experimentation.

China’s advantage lies in its willingness to deploy early, accept imperfections, and improve through use. Speed, cost control, and manufacturing scale form a powerful combination.

Speed to deployment is the
new competitive edge in
robotics.

Challenges Still Limit Mass Adoption

Despite rapid progress, significant hurdles remain. Humanoid robots Chinese or otherwise still face:

• Limited battery life

• Long-term reliability concerns

• Safety certification challenges

• Workforce acceptance issues

• Integration complexity with existing systems

Humanoid robots are not yet plug-and-play solutions. Their industrial adoption will depend on continued improvements in robustness, maintenance, and total cost of ownership.

Export markets also impose stricter compliance and regulatory requirements, particularly in Europe and North America.

A New Phase in Industrial Robotics

What is unfolding in China is not a sudden breakthrough, but a structural shift in strategy. Humanoid robots are moving from speculative R&D projects to industrial products subjected to market discipline.

This transition mirrors earlier phases of robotics evolution, where initial skepticism eventually gave way to widespread adoption once cost, reliability, and usefulness aligned.

Humanoid robots may not dominate factories tomorrow but they are no longer science experiments.

When Execution Becomes the Competitive Edge

The journey from prototype to factory floor defines the next chapter of humanoid robotics. Chinese industrial players are not claiming to have solved every technical challenge. Instead, they are proving something arguably more important: humanoid robots can be built, deployed, and improved in real industrial contexts.

In this race, technological brilliance alone is not enough. Execution speed, manufacturing capability, and learning through deployment are becoming decisive advantages.

For the global robotics industry, the lesson is clear. The future of humanoid robots will not be decided only in laboratories but on factory floors, where practicality ultimately outweighs promise.

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Safety as an Industrial Foundation

European industry has been built around a core principle: machines must adapt to humans not the other way around.

Standards promoted in particular by the International Organization for Standardization (ISO) have enabled the rise of collaborative robots, secure cells, and advanced control systems.

The results:

• Stronger social acceptance

• Reduced legal risks

• Better integration into existing industrial sites

In robotics, Europe has made a
strategic choice: prioritizing safety
and trust over speed at all costs.

European Regulation: A Barrier… That Protects

European regulation acts as a quality filter. It imposes high requirements in terms of functional safety, liability, and traceability.

In the short term, this can slow down certain deployments. In the long term, it creates a structural advantage for players capable of complying with these standards.

European industrial companies know that a solution certified today will be exportable tomorrow, without major regulatory reassessment.

In Europe, for example, CE marking forms the regulatory foundation for placing any robot on the market whether industrial, collaborative, or humanoid. It certifies that the manufacturer has carried out a comprehensive risk assessment, that the machine meets essential requirements for safety, health, and personal protection, and that it complies with harmonized European standards.

With the entry into force of the EU Machinery Regulation 2023/1230, the CE framework is evolving to better integrate autonomous robots, connected systems, and embedded AI, strengthening requirements related to functional safety, cybersecurity, and traceability. In a context of growing robot deployment in open environments, CE marking is becoming a key factor of trust and industrial acceptability far beyond a simple administrative obligation.

What the United States and China Can Learn

The United States excels in innovation speed and software scalability.
China masters industrial capacity, cost reduction, and rapid scaling.

However, both models are now facing limitations:

• Social acceptability

• Liability in the event of incidents

• Deployment in sensitive environments

The European model offers a complementary answer: trust as an industrial asset.

The next robotics revolution will
not be purely technological it will
be regulatory and societal.

Towards a Convergence of Models

Rather than competing approaches, global robotics may evolve toward cooperation between models:

• The United States brings software innovation and AI

• China brings industrial capacity and speed

• Europe brings standards, safety, and governance

This convergence is essential to deploy robotic systems at scale in complex and highly regulated environments.

Robotics is entering a phase of maturity. In this context, trust is becoming as strategic as performance. By placing standards, safety, and regulation at the heart of its approach, Europe is not slowing the market it is preparing its global sustainability. The United States and China would be well advised to draw inspiration from this model and build alongside it.

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A technology ahead of its system

Humanoid robotics has reached a level of technical maturity that would have seemed unrealistic only a decade ago. Advances in artificial intelligence, perception, locomotion, and manipulation have enabled robots to walk, grasp, learn, and adapt in increasingly complex environments. Supported by progress in computing power, sensors, and foundation models, humanoid systems are now capable of executing tasks that closely resemble human actions.

Yet despite this progress, large-scale industrial deployment remains limited. Most humanoid robots are still confined to pilots, demonstrations, or tightly controlled experimental settings. The issue is no longer whether humanoid robots can function, real question is why they are not scaling.

The answer lies less in technology than in structure. Humanoid robotics is encountering a system-level bottleneck.

A coordination problem, not a capability gap

Across manufacturing, logistics, healthcare, and services, a recurring pattern emerges: the ecosystem surrounding humanoid robotics is fragmented. The key actors involved in deployment operate with different priorities, assumptions, and timelines.

Technology developers tend to focus on performance metrics such as dexterity, autonomy, learning speed, and adaptability. Industrial operators prioritize reliability, safety, integration with existing processes, and accountability. Investors evaluate scalability, narratives of disruption, and long-term market dominance. Regulators, insurers, and standards bodies focus on risk management, certification, and responsibility.

Each of these perspectives is internally coherent. The problem is their misalignment. Humanoid robotics currently lacks a shared operational framework that connects these actors into a functioning system. Without coordination, progress in one domain does not translate into adoption in another.

Humanoid robotics is no longer
limited by technology. It is constrained
by the system around it.

Lessons from collaborative robots

The contrast with collaborative robots, or cobots, is instructive. Cobots did not succeed because they were the most advanced robots available. They succeeded because the conditions for adoption were clear.

Safety standards were established early. Use cases were narrowly defined. Return on investment was measurable. Integration costs were predictable. Responsibilities were clearly allocated between manufacturers, integrators, and operators.

Humanoid robots, by contrast, aim to be general-purpose systems capable of adapting to multiple tasks and environments. This ambition places them in a fundamentally different category. Rather than tools, humanoids resemble infrastructure.

Infrastructure does not scale through demonstrations alone. It scales through standards, contracts, insurance models, and accepted failure modes. Until these elements are in place, even the most capable humanoid systems will struggle to move beyond experimentation.

The missing operating model

One of the most significant obstacles to deployment is the absence of a widely accepted operating model for humanoid robots. Basic questions remain unresolved across industries:

Who is responsible when a humanoid robot fails or causes damage? How is uptime defined and guaranteed and tasks certified as suitable for humanoid execution? How is operational risk priced and insured?

In traditional industrial automation, these questions are answered through decades of accumulated standards and practices. For humanoids, the answers are still emerging. As a result, many industrial actors perceive humanoid deployment as an open-ended risk rather than a controlled investment.

This uncertainty explains why numerous pilot projects fail to progress into scaled deployments. The technology may be ready, but the surrounding system is not.

From spectacle to reliability

Public discourse around humanoid robotics often emphasizes spectacle: lifelike movement, human-like interaction, and futuristic demonstrations. While these elements capture attention, they are not what drives industrial adoption.

Industries adopt systems that are predictable, reliable, and boring. Reliability matters more than novelty. Accountability matters more than performance peaks. Predictability matters more than versatility.

For humanoid robots to become viable at scale, the narrative must shift from disruption to dependability. The focus should move from what humanoids could do to what they can do consistently, safely, and economically over time.

What the industry should prioritize next

If humanoid robotics is to move beyond its current plateau, the next phase of development must focus on coordination rather than capability. Several priorities stand out.

First, use cases must be narrowly defined and repeatable. Controlled environments with stable processes offer the most realistic starting points. Attempting to solve too many problems at once increases uncertainty and slows adoption.

Second, shared deployment standards are essential. Safety certification, liability allocation, and operational responsibility need to be clarified early. Without these foundations, industrial actors will remain cautious.

Third, incentives across the ecosystem must be aligned. Developers, operators, insurers, and regulators need shared expectations regarding performance, risk, and timelines. Fragmented incentives lead to fragmented outcomes.

Finally, deployment strategies should emphasize integration over disruption. Humanoid robots are more likely to be adopted when they complement existing systems rather than attempt to replace them wholesale.

Reliability matters more than
novelty. Accountability matters
more than performance peaks.

Humanoids as emerging infrastructure

Seen through this lens, humanoid robots are not failed products or overhyped concepts. They are emerging infrastructure that has not yet found its operating rules.

Infrastructure adoption follows a different trajectory than consumer technology. It requires patience, coordination, and institutional alignment. Once established, it becomes invisible, embedded, and indispensable.

Humanoid robots will not scale because they are impressive. They will scale when they become unremarkable  when their presence no longer raises questions about safety, liability, or feasibility, but is simply part of how work gets done.

A systemic transition ahead

The next chapter of humanoid robotics will be shaped less by breakthroughs in hardware or AI than by progress in coordination. The challenge ahead is not to build better robots, but to build a system capable of deploying them.

Those who succeed will be the actors who understand humanoid robotics not as a standalone technology, but as a system that must be designed, governed, and aligned.

The transition from experimentation to infrastructure has begun. Whether it accelerates will depend on how quickly the ecosystem learns to coordinate itself.

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