---
description: >-
  Humanoid robots will reshape the global economy. We expect a 10x growth
  annually for the next six years. By 2029, over 10 million humanoid robots will
  be active in factories, warehouses and homes.
---

# The 10x Thesis

Crypto is often regarded as one of the fastest-adopted technologies in modern history, largely due to its decentralized nature, global accessibility, and the rapid growth of blockchain infrastructure. In just over a decade, it grew from a niche concept into a trillion-dollar industry, reshaping finance, technology, and culture. Its adoption was fuelled by a combination of speculative interest, technological innovation, and the promise of disrupting traditional systems.

However, one technology has outpaced even crypto in deployment speed: Large Language Models (LLMs). OpenAI’s ChatGPT reached 100 million users in just two months, a milestone that took crypto years to achieve.

We project that the number of operational humanoid robots will grow from around 1,000 in 2025 to 10 million by 2029. Yes, you read that right. **Humanoid robots are on track for a 10x annual growth rate over the next six years,** mirroring semiconductor scaling laws. Besides Digital AI, there will be nothing growing at a faster rate.‍

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#### We Are in the Explosion Phase. A Period of Tremendous Opportunity

In our first thesis, [“The rise of humanoid robots and Physical AI”,](https://www.xmaquina.io/blog/the-rise-of-physical-ai) we presented four phases that represent the different stages of development of the humanoid robotics ecosystem. After decades of research, we are entering the explosion phase, which will last between 5 to 10 years. In this phase, we will experience an explosion of new manufacturers, new technology providers, and new subsidiaries from larger technology companies, solely working on the humanoid robotics space. It will be a wild, wild west for a few years with not a single company or ecosystem dominating.

This phase offers tremendous opportunity for innovation, investment, and market growth as companies compete to define the standards and applications of humanoid robotics. The fragmentation of the market during this period could lead to the development of diverse solutions tailored to various industries, potentially leading to significant technological breakthroughs and the establishment of new market leaders.

#### The Drivers of 10X Annual Growth

This detailed review explores what might unfold during the explosive phase and examines the key factors fuelling unprecedented progress in humanoid robotics.

Are there signs that high-volume growth is possible, even likely?

**Yes, there is. Here’s how we see the future unfolding.**

## Phase E1 (2025-2026)

### **Industrial Proof of Concept: The First 10K Daily Active Humanoids**

We are witnessing the deployment of the first humanoid robots in industrial use cases. Tesla’s Optimus Gen 3 robots are set to be deployed in factories, with the company’s Q3 2025 production target of 3,000 units primarily addressing internal needs, automating battery cell sorting and component assembly at Gigafactories.

Meanwhile, Agility Robotics’ Digit v3 and Sanctuary AI’s Phoenix systems are achieving 98% reliability in warehouse logistics, adeptly handling over 800 package types for Amazon and Walmart distribution centres. Figure AI has also reached a major milestone, signing an agreement with BMW to integrate humanoid robots into automotive production. While likely a proof of concept, this move signals serious industry interest in testing revolutionary technology. Figure AI is in talks to raise $1.5 billion at a $39.5 billion valuation to accelerate production, underscoring confidence in scaling these innovations.

By late 2026, three significant benchmarks should be crossed:

1. **The $40K Price Range**: Elon Musk has suggested Tesla’s Optimus could retail between $20,000 and $30,000 by 2025 or 2026, aligning with consumer and industrial affordability goals. Figure AI’s, Figure 03 model is estimated at $30,000 to $150,000, reflecting its advanced commercial focus, while Unitree Robotics offers the Unitree G1 at a striking $16,000, though the full price, including all necessary options, remains unclear. We are a little less optimistic on that front, as we expect the starting price for humanoid robots to be closer to $40,000 with a monthly operating cost close to the vicinity of $2,000. However, this is unlikely to hinder the adoption of early proof-of-concept deployments, as industrial and research sectors will prioritize functionality and long-term savings over upfront costs.\
   ‍
2. **Autocatalysis**: Between 10% and 20% of new robot production could involve existing robots assembling their successors, establishing a self-sustaining growth cycle. Such a development would mark a tipping point in manufacturing, where the scalability of humanoid robots begins to mirror the exponential growth seen in other automated systems, cutting production costs dramatically over traditional methods.\
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3. **Spatial Intelligence**: Humanoid robots in factories should reach a level 4 of autonomy comparable to highly advanced self-driving vehicles. This advancement will enable them to operate alongside human workers in structured environments, efficiently navigating complex spaces with little oversight. Ensuring safety will be a top priority, achieved through cutting-edge sensors, instantaneous obstacle detection, and adaptive systems that allow robots to adjust to human presence. This breakthrough will lay the foundation for wider integration in workplaces where accuracy and human-robot collaboration are essential.

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### **The Main Use Cases: Working Factories and Warehouses**

These initial deployments showcase factory automation and warehouse logistics as key applications driving early growth. Their success will demonstrate that humanoid robots are practical solutions for repetitive, labor-intensive tasks. In factories, humanoids are being assigned roles such as assembling components, operating machinery, and performing quality checks—tasks that require precision and endurance rather than creativity or improvisation.

These jobs are inherently mechanical, which is exactly what machines excel at. Additionally, factories and warehouses provide controlled environments with fixed layouts, clear workflows, and minimal unexpected variables, making them ideal testing grounds for humanoid robotics.

**End Of 2026: 10,000 Daily Active Humanoids**

By late 2026, we project 10,000 humanoid robots will be active daily across these industrial settings. This figure assumes a steady ramp-up from pilot programs in 2025, driven by companies like Tesla (with Optimus), Figure AI (with Figure 03), and Unitree Robotics (with the G1).

Tesla’s Fremont “Bot Foundry” could contribute a few thousand units, leveraging its expertise in high-volume production, while Amazon’s logistics network—already a leader in robotic automation—might account for a significant share as it integrates humanoids into its fulfillment centres. Smaller players, including startups and regional manufacturers, will likely fill the gap, targeting niche factory tasks like electronics assembly or food processing.

### **Bold Predictions**

**Physical AI will improve faster than expected.**

The software powering these humanoid robots is likely to progress at a much quicker pace than the hardware. An AI system akin to a hypothetical “Helix”—capable of real-time spatial reasoning, task prioritization, and human-robot collaboration—could become the key differentiator.

While hardware improvements, such as battery life and joint durability, will advance gradually, breakthroughs in machine learning and sensor fusion could enable robots to adapt to varied tasks and environments with minimal reprogramming. This agility will amplify their value, especially in warehouses where inventory layouts might shift regularly.

**Amazon will announce its own humanoid robots.**

Amazon has been a leader in warehouse automation for years, with over 750,000 robots in operation by 2025, handling tasks like picking, packing, and sorting. As early as 2023, Amazon began testing humanoid robots in its U.S. warehouses, including “Digit,” developed by Agility Robotics. The company also has the Amazon Industrial Innovation Fund, a $1 billion venture capital initiative launched in April 2022 to support emerging technologies. Agility Robotics was one of the fund’s first recipients. More recently, in February 2024, Amazon contributed $50 million to Figure AI’s $675 million Series B round.

Given how essential automation is to Amazon’s operations—and with humanoid robots becoming the next step in scalable, adaptable labor—we expect the company to announce its own humanoid robots soon. This could happen through an acquisition or the launch of an in-house program. Similar to how Amazon Web Services (AWS) started as an internal tool before growing into a dominant cloud provider, Amazon would likely first use these robots in its own warehouses. Picture them working alongside humans, handle packages, and even assist with last-mile deliveries. Over time, Amazon would refine their design, durability, and software, using real-world data from its vast logistics network before making them available to external customers.

We also anticipate heavy investment in supporting infrastructure. Amazon will likely integrate these robots with its cloud ecosystem, building on AWS to provide real-time data processing, spatial intelligence, and predictive maintenance capabilities. They could introduce incentive mechanisms—such as leasing models or pay-per-task pricing—to entice partners and customers into adopting this technology. This end-to-end solution, combining hardware, software, and data services, would position Amazon not just as a user of humanoid robots but as a dominant player in their commercialization. We predict Amazon will make this announcement in 2026, with mass deployment occurring later, in 2028 or 2029.\
‍

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## Phase E2 (2027-2028)

### **Large Scale Industrial Deployment Will Lead to One Million Humanoid Machines**

The successful proof-of-concept trials from 2025-2026 will build widespread confidence, driving a sharp increase in demand from new customers eager to adopt humanoid robotics. Industrial deployments will expand rapidly, both in scale and the range of tasks they can handle. Early pilots will generate valuable data and operational insights, allowing manufacturers to improve every aspect of humanoid robots—making them more reliable, efficient, and adaptable.

Tesla’s Optimus, for example, could surpass 50,000 units per year as production accelerates, while Agility Robotics and Sanctuary AI expand their warehouse solutions to handle more unpredictable tasks. Figure AI’s partnership with BMW could transition into full-scale automotive assembly lines, applying lessons from initial trials to improve precision and speed. This phase will be a turning point, with costs nearing $25,000 per unit, modular chassis systems allowing for task-specific customization, and cloud robotics improving overall fleet coordination.

1. **Improved Autocatalysis**:  By 2028, more than 30% of new robots could be built by existing robots, creating a self-sustaining production cycle. Tesla’s fully automated lines may reach over 5,000 Optimus units per month, while Figure AI scales its facilities to keep up. This shift is likely to reduce reliance on human labor, speed up production, and allow manufacturers to scale output quickly to meet rising demand.

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2. **Battery Advancements**: Energy density breakthroughs, such as Tesla adopting next-gen 4680 cells (potentially 300+ Wh/kg) or partnering with QuantumScape for solid-state QSE-5 successors (800+ Wh/L), will extend runtimes to 12-16 hours per charge. Fast-charging infrastructure (15-20 minutes) could minimize downtime, making robots viable for continuous industrial use and supporting expansion into outdoor or remote applications.\
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3. **Standardized Modular Systems**: Robotics companies will adopt standardized modular designs to simplify maintenance and operations. Swappable components, including key body parts, will make repairs and upgrades more efficient. More importantly, interchangeable battery systems will help offset runtime limitations, ensuring minimal downtime and keeping robots in continuous operation.\
   ‍
4. **AI Orchestration and Cloud Robotics**: Advanced AI systems will orchestrate fleets of hundreds of robots. Drawing from Tesla’s Dojo supercomputing or Sanctuary AI’s distributed intelligence, these platforms will optimize task allocation, predictive maintenance, and real-time learning. For example, a factory could deploy 200 Optimus units under a single AI control centre, dynamically adjusting workflows to meet production demands while improving efficiency and scalability.\
   ‍
5. **Expanding Use Cases**: As the primary applications are proving viable, new sectors like construction will start their first experiment. We expect that this will start with relatively low volume but the awareness that it will bring to the space will be significant. This will inspire new development and new robotics companies to be formed.

AI orchestration and cloud robotics is going to be critical for market growth during this phase. As companies begin deploying fleets of 500 or more robots in a single factory, managing them efficiently will become a necessity.  They will need intuitive systems to onboard and decommission units, assign tasks and locations, and diagnose issues—all in real time.

By 2028, we anticipate third-party vendors offering cross-platform orchestration software. In the proof-of-concept phase, manufacturers can provide hands-on support for small deployments, but large-scale industrial rollouts will require automated, turnkey solutions. For example, a BMW plant running 600 Figure 04 units and 200 Apptronik A3 units could use a cloud-based dashboard to shift robots from chassis assembly to quality inspection in under 30 minutes. These systems will manage robots from different manufacturers and predict maintenance needs based on wear patterns logged over 10,000+ operational hours.

This level of scalability and efficiency is what we expect will turn early adopters into long-term users. It’s also possible that Amazon will introduce a cloud-based robot management platform before deploying its own humanoid robots.

### **The Main Use Cases: Factory and Warehouse Logistics**

Factory automation and warehouse logistics are expected to remain the leading applications, benefiting from controlled environments and repetitive, labor-intensive tasks. While humanoid robots could theoretically run 24/7, battery life and maintenance cycles will likely limit operation to 18-20 hours per day by 2028. Improvements in both hardware and software will continue to accelerate, allowing robots to handle heavier payloads, complete tasks faster, and integrate more seamlessly with human workers—laying the groundwork for wider industrial adoption.

**End of 2028: 1,000,000 Daily Active Humanoids**

By late 2027, we anticipate 100,000 humanoid robots operating daily—about 10 times the number in 2026. If this exponential growth continues, the total could reach 1 million by the end of 2028.

This projection assumes Tesla, Figure AI, Agility Robotics, and potential new entrants like Amazon will each produce 200,000 to 300,000 units annually, driven by automated assembly and lower manufacturing costs. At this scale, these robots could collectively perform the equivalent of 20 million human labor hours per day, fundamentally reshaping industries and labor markets.

### **Bold Predictions**

**Sodium-Based Battery Breakthrough**: A sodium-based, solid-state battery could emerge by 2028, offering 900+ Wh/L at half the cost of lithium-ion equivalents. While not yet mass-produced, early prototypes—possibly from CATL or a startup like Natron Energy could power a small fleet of robots for 20+ hours per charge. This would slash operating costs by 30% and trigger a wave of investment in energy-dense alternatives, accelerating robot economics.

**Amazon’s Humanoid Debut**: Amazon is expected to introduce its first in-house humanoid robot in 2028, designed specifically for warehouse-to-delivery operations. With a streamlined, lightweight build and AWS-powered orchestration, it could see an internal deployment of 50,000 units by the end of the year. A commercial version may follow, targeting warehouses, logistics providers, and last-mile delivery companies.

**Cross-Vendor AI Standard**: By 2028, a consortium of robotics companies is expected to introduce an open-source AI orchestration protocol. With adoption projected to reach 70% of the market, this standard will allow seamless fleet management across different brands, accelerating humanoid robot deployments beyond 2 million units by 2030. This aligns with our earlier predictions on the [rise of humanoid robots and Physical AI](https://www.xmaquina.io/blog/the-rise-of-physical-ai) in our first essay.

## Phase E3 (2029-2030)

### **First Outdoor Use Cases Eyeing 50 Million Daily Active Humanoids**

Phase E3 will be a critical turning point—the first real push to take humanoid robots beyond industrial settings and into less predictable, consumer-focused environments. This stage will introduce them into retail stores, select homes, and outdoor spaces, moving them from purely industrial tools to something closer to an everyday assistant. However, this transition will bring new challenges. Operating in uncontrolled environments with untrained users will create risks in safety, reliability, and public acceptance. Exposure to dust, weather, and human unpredictability will test hardware durability, while intuitive interfaces and fail-safes will be crucial to prevent accidents or misuse.

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The exponential growth may decelerate as companies grapple with technical and societal barriers. We expect that the 10X per year, will be replaced by a 7X per year. Regulation will loom large, especially in highly regulated sectors like hospitals, homes, and public spaces.

Countries such as Japan and Singapore may move quickly to approve robots for eldercare and urban maintenance, while the U.S., EU, and China could experience delays due to strict safety, privacy, and labor regulations. Some nations may resist adoption entirely, enforcing bans or heavy restrictions that slow global standardization.

To sustain this expansion, both hardware and software ecosystems will need to scale significantly. Just as mobile operators rolled out mobile networks to deliver seamless connectivity in a country, humanoid operators will deploy, manage, and support vast fleets of robots within specific regions or countries.

**The 50M units milestone by 2030 will be propelled by:**

1. **Fully Autonomous Production**: Autocatalysis will peak, with over 70% of new robots built by robotic assembly lines. Tesla’s Fremont “Bot Foundry” and Figure AI’s scaled facilities could churn out 50,000+ units monthly, meeting surging demand while driving unit costs to unprecedented lows.\
   ‍
2. **Standardized Modular Systems**: Standardized modular designs will allow for rapid customization. Robotics companies and third parties could offer interchangeable components, e.g., reinforced legs for heavy lifting or precision grippers for assembly, reducing redesign costs and enabling on-site adaptability. This flexibility will accelerate deployment across diverse industries, from automotive to retail.\
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3. **Modular Ecosystem Expansion**: Modular chassis systems will evolve into a plug-and-play standard. Companies like Clone Robotics and Agility Robotics could offer swappable modules (e.g., heavy-duty legs for construction, dexterous arms for caregiving), supported by a thriving aftermarket of third-party accessories, much like smartphone cases or apps.\
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4. **Energy Independence**: Battery innovations, such as QuantumScape’s QSE-5 successors (potentially exceeding 1,000 Wh/L) or sodium-based solid-state cells, will enable 24+ hour runtimes and 15-minute charges. Wireless charging pads, akin to EV stations, will proliferate in homes and workplaces, ensuring robots remain untethered and operational.\
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5. **Humanoid Operator Networks**:  Regional “humanoid operators,” similar to telecom providers like Verizon or Vodafone, will customize robot fleets to meet local demands. In Japan, the focus may be on eldercare, while in the U.S., urban delivery could take priority. These operators will handle maintenance, 24/7 customer support, teleoperation, financing (leasing at $300-$500 per month), and recycling, creating a full-service ecosystem. For example, a Scandinavian operator might service IKEA’s warehouse robots while leasing home units, bundling them with cloud subscriptions—much like telecom companies do with data plans.\
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6. **AI Orchestration at Scale**: AI orchestration will mature into cloud-based “robot OS” platforms, managing millions of units globally. These systems will enable seamless updates, skill downloads (e.g., cooking, tutoring), and fleet coordination, turning individual robots into nodes in a networked intelligence ecosystem.

During this phase, we expect that tele-operations will be critical. Humanoid operators will collaborate with specialized skilled workers who can remotely control robots for two main reasons: to assist humanoids that become stuck in difficult situations and, more importantly, operate humanoids to do things that are totally new and unexpected. The data collected from these remote operations will be highly valuable, helping robots gradually develop the ability to handle such situations on their own.

### **End of 2030: 50 Million Daily Active Humanoids**

From 7 million daily active humanoid robots at the end of 2029, growth will surge to 50 million by late 2030. Industry leaders like Tesla, Amazon, and Figure AI, alongside emerging players, could each deploy 5-15 million units annually, supported by humanoid operator networks spanning 50+ countries.

Collectively, these robots could perform 1.2 billion human-equivalent labor hours daily, equivalent to the output of over 50 million full-time workers—fundamentally reshaping work, leisure, and societal structures worldwide. Remarkably, this deployment volume will nearly match the global annual sales of automobiles, which currently hover around 60 million units, underscoring the scale and speed of this robotic revolution.

### **Bold Predictions**

**1. Apple’s “iHuman” Launch**: We anticipate Apple will introduce the “iHuman,” a consumer-focused humanoid robot, by 2030. Similar to how the Vision Pro debuted in 2023 as a high-end test platform, the iHuman will showcase Apple’s signature design and ecosystem integration.

Priced around $29,500, it will cater to affluent households and small businesses, featuring intuitive voice control, a sleek minimalist design, and modular “Apple-certified” accessories. Apple may also collaborate with a humanoid operator—possibly a revamped AT\&T or a new entity—to manage deployment, maintenance, and a subscription model ($800/month), much like the iPhone’s 2007 carrier partnership.

<figure><img src="https://cdn.prod.website-files.com/6763dfa8120b46189e3e1a35/67c729a751f1c1aae53be58d_1740839566566.jpg" alt=""><figcaption></figcaption></figure>

**2. Mobile Operators becoming Humanoid operators**: Telecom giants like Verizon, Vodafone, and T-Mobile will compete to become leading humanoid operators, recognizing this role as key to the widespread adoption of humanoid robots. We anticipate a mixed outcome: some will successfully adapt, revitalizing their business models, while others will struggle to meet the unique demands of robotics.

Mobile operators hold key advantages: they control the data pipeline, crucial for cloud-connected robots, boast retail stores nationwide for sales and support, and, in some cases, employ technical personnel ready to pivot from cell tower repairs to robot maintenance. For example, a firm like AT\&T could deploy 100,000 robots in the U.S., offering bundled “robot + 5G” plans, while a less agile competitor might stumble over software integration or customer service gaps.**‍**

**3. A Robotics company becomes the largest company in the world**: By 2030, the world’s largest market capitalization will belong to a company centred on humanoid robots—likely Tesla, NVIDIA, Apple, or a still private startup.

Tesla’s edge lies in production scale and AI, potentially pushing its valuation past $5 trillion. NVIDIA could surprise everyone with the delivery of their own humanoid robots. Meanwhile, a new player, possibly the result of a merger between Figure AI and Agility Robotics, could reach a $3 trillion valuation by perfecting modular ecosystems and operator networks.**‍**

**4. Global Robot Tax Debate**: By late 2030, a “robot tax” will spark global controversy as 50 million humanoids start having an impact on manual jobs globally. Left-leaning nations like Sweden and Canada might impose a $1,000-per-unit annual levy to fund universal basic income, generating $50 billion yearly, while free-market nations resist, arguing it stifles innovation.**‍**

**5. Android robots**: By 2030, the world will witness the unveiling of the first mass-market androids: highly advanced, human-like humanoid robots designed for widespread consumer and industrial use. These androids, will blur the lines between human and machine, echoing the dystopian yet mind-blowing visions of Blade Runner and Westworld.

With lifelike appearances, and capabilities for emotional interaction, these androids will be marketed for roles ranging from personal assistants and caregivers to entertainment performers, targeting a global market of over 100 million units by 2035.**‍**

**6. Space Robotics** : By 2030, SpaceX will unveil its plan to deploy hundreds of humanoid robots on the Moon or Mars, designed to withstand extreme conditions with radiation-resistant circuits and solar-powered batteries.

These “AstroBots” will assist in constructing habitats and extracting resources. In hindsight, it will become clear that this was Elon Musk’s plan all along: developing humanoid robots not just for use on Earth, but as a key technology for terraforming other planets and preparing humanity for a multi-planetary future.

<figure><img src="https://3845795905-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fet8WTC8isg8YGzzdTqga%2Fuploads%2F9awyl8zjqzcx6vO2byjB%2F67c75c1fd19b59563c9f6e5e_1740840496341.jpg?alt=media&#x26;token=c144c257-5068-42da-837a-16a8b1aa16e7" alt=""><figcaption><p>The Tesla "Optimus Prime" </p></figcaption></figure>
