Why the humanoid robot industry struggles to prove real profitability

Manufacturers are shifting their focus from how many units they ship to how much actual work their machines perform. As the industry moves from laboratory demonstrations to warehouse floors, companies are struggling to bridge the gap between massive production numbers and genuine commercial profitability. This shift is essential because current metrics often fail to show if a humanoid robot actually pays for itself through labor savings.
- Interact Analysis reported in June that only about 10% of the 20,000 robots produced globally in 2025 reached real-world applications.
- China's AGIBOT introduced a new metric called Worken on October 29 to measure "effective intelligent work hours."
- The Chinese government issued a directive in June 2026 requiring state-owned enterprises to deploy robots by December 31.
Why is the industry struggling to prove robot productivity?
The robotics sector currently lacks a common yardstick to compare different machines. While some companies report how many hours a machine operates, others focus on how many items it moves or how many units they have sold. This makes it difficult for buyers to know if a robot is a good investment.
According to pymnts.com, existing data points are often incomparable. For instance, Agility Robotics reported that its Digit humanoid moved over 100,000 totes at a Georgia warehouse with 98% accuracy. Meanwhile, Figure AI reported that its Figure 02 robots handled more than 90,000 sheet metal cycles at a plant in South Carolina. One company measures totes while the other measures metal cycles, making a direct comparison impossible.
AGIBOT is attempting to solve this by using a score called Worken. This metric calculates "effective intelligent work hours" by multiplying active robots by their autonomous hours and an efficiency ratio. This ratio compares the robot's output against a human benchmark. This approach ensures that two fleets of the same size are not treated as equal if one requires constant human help to finish tasks.
Is there a gap between production and real use?
There is a massive disconnect between the number of machines being built and the number of machines actually working in factories. While production is exploding, most of these machines are used for research or entertainment rather than making money for businesses.
Research from techtimes.com notes that global production jumped tenfold from under 2,000 units in 2024 to over 20,000 in 2025. However, the vast majority of these units are not in commercial service. China's manufacturers produced more than 90% of that total volume.
Unitree's own filing ahead of its August listing on the Shanghai STAR Market showed that more than 70% of its revenue came from educational and research customers. Only less than 10% of its sales came from industrial applications. This suggests that the industry is currently building tools for scientists rather than tools for workers.
How much does it cost to deploy these machines?
The high cost of hardware remains a major barrier to widespread adoption. For a robot to be useful in a factory, the price must drop significantly to allow the machine to pay for itself within a reasonable timeframe.
Current Chinese models sell for between 300,000 and 500,000 RMB, which is roughly $44,600 to $74,400 per unit. To achieve a two-year payback period, the price needs to fall toward 160,000 RMB, or about $23,800. This is a manufacturing challenge rather than just a technology problem.
Even if a robot performs well, it may not be profitable. The Worken metric proposed by AGIBOT does not include costs like electricity, maintenance, or integration. A robot might have a high productivity score but still cost more to operate than the human worker it replaced.
How each side tells it
The industry is split between those focusing on rapid technological growth and those focusing on the economic reality of deployment.
AGIBOT views the current era as a transition toward selling results rather than hardware.
"2026 marks the beginning of large-scale deployment for embodied intelligence,"said AGIBOT's senior vice president.
On the other hand, market analysts highlight the "impossible triangle" that companies must solve. To succeed, a machine must provide autonomous operation, a clear return on investment, and the ability to handle many different tasks at once. Currently, most machines struggle to do all three.
How is China forcing robot adoption?
China is moving away from a market-driven approach and toward a government-mandated approach to ensure robots move into the real world. The goal is to generate the massive amounts of data needed to train more advanced artificial intelligence.
In June 2026, the Chinese Ministry of Industry and Information Technology and the State-owned Assets Supervision and Administration Commission issued a directive. They ordered local governments and state-owned enterprises to deploy these systems into real operations by the end of the year. The target is more than 10,000 units across 100 different scenarios, including healthcare and logistics.
This mandate is a procurement instruction. By forcing state-owned companies to buy robots, the government ensures that machines collect physical interaction logs. These logs are vital because, unlike text-based AI, physical robots need to record how they move and interact with objects to improve their intelligence.
What happens next?
The industry faces several immediate deadlines and milestones. In China, local governments must submit their implementation plans for robot deployment soon, and progress reports are due in November 2026. The official deadline for the government-mandated deployment is December 31, 2026.
In the United States, Agility Robotics is moving toward public markets. Shareholders of Churchill Capital Corp XI approved a merger with Agility, and the combined company is expected to start trading on the Nasdaq on Thursday, November 5. These market movements will provide more data on whether investors believe the robots can actually generate profit.
Frequently Asked Questions
Why are robot companies not focusing on profit yet?
Most companies are currently in a phase of gathering data and proving technical capabilities. They are prioritizing the ability to perform tasks reliably before they can prove the machines will save more money than they cost.
What is the difference between a robot being "active" and "productive"?
An active robot is one that is turned on and moving, while a productive robot is one that completes tasks successfully without needing a human to step in and fix errors.
Will humanoid robots replace human workers soon?
While they are being deployed in warehouses and factories, high costs and the need for constant data collection mean they are currently more common in research labs than in general labor roles.


