In 2026, embodied intelligence has made significant progress in the industrial field.
Start-up company Shi Zhihang’s A1 robot set a Guinness world record by completing more than a hundred submillimeter level automotive wiring harness plugging operations in one hour.
Automotive wiring harness assembly has always been a problem in the field of industrial automation. Because the wiring harness is flexible and easy to deform, the jack gap is only 0.1 –
0.5mm. In the past few decades, it could only rely on manual operation by skilled workers. It is known as the “Goldbach’s conjecture” in the field of industrial automation.
This breakthrough of the A1 robot has become a landmark node for embodied intelligence to move from the laboratory to the industrial scene.
Currently, embodied intelligence has been commercially verified in multiple industrial scenarios.
In the production lines of new energy vehicle companies, robots from UBTECH and other companies have been deployed in batches to complete quality inspection, labeling, and material transfer tasks between workstations, adapting to the factory’s narrow channel traffic needs.
In 3C electronics manufacturing scenarios, robots can complete processes such as force-controlled assembly of memory modules and gluing of electric drive casings, with a repeatable positioning accuracy of ±0.05mm, meeting the high-precision production requirements of consumer electronics.
In scenarios such as warehousing, chemical industry, and electric power, robots undertake long-cycle inspections and standardized handling tasks, with a task success rate of more than 90% in structured industrial scenarios.
The domestic embodied intelligence industry will annually grow by more than 50% from 2025 to 2026. In 2025, the sales volume of UBTECH industrial humanoid robots will reach 1,079 units, corresponding to 820 million yuan in revenue, and stable commercial delivery capabilities have been formed.
Compared with traditional industrial robots, embodied intelligence has obvious differences.
Traditional industrial robots are like students who can only answer fixed questions. All actions must be programmed in advance. They can only cover about 30% of fully standardized manufacturing processes. The remaining 70% of non-standardized processes in small batches and varieties cannot be automated and rely on manual labor for a long time.
Embodied intelligence is equivalent to a skilled worker who can draw inferences from one example. It does not require task-by-task customized programming. It can dynamically sense the environment and autonomously dismantle tasks, directly adapting to the original human working environment without the need for large-scale transformation of the production line layout. It also supports non-isolated collaborative work with workers in the same space, which just fills the gap that traditional automation solutions cannot cover.
However, the industry is still in the transition stage from small-scale pilots to large-scale implementation, and the core stuck points are concentrated in three dimensions.
First, there is a huge data gap. Training general industrial embodied large-scale models requires at least tens of millions of hours of multi-modal interactive data. Currently, the industry-wide average monthly output of high-quality data is only 250,000 to 300,000 hours, resulting in a serious imbalance between supply and demand.
Second, the model has insufficient generalization. A model trained on a single production line almost needs to be retrained after being migrated across scenarios. Cumulative errors are prone to occur when executing long sequence tasks, and deviations in any sub-step may cause the overall task to fail.
Third, the deployment cost is still high. The comprehensive cost of hardware body + data collection + customized training is higher than that of traditional industrial robotic arms, which is temporarily difficult for small and medium-sized manufacturing enterprises to afford.
However, my country has included embodied intelligence as one of the six future industries in the forward-looking layout of the “15th Five-Year Plan”. In June 2026, the first embodied intelligence industry standard was officially implemented, clearly listing task success rate, execution efficiency, manual intervention rate, etc. as core evaluation indicators for industrial scenarios. The industry has entered the stage of standardized implementation.
Hangzhou, Beijing and other places have established national-level pilot bases to build public computing power, data openness, and scenario verification platforms to lower the technology iteration threshold for small and medium-sized enterprises.
The entire industry generally predicts that 2027-2029 will usher in a large-scale inflection point: by then the domestic replacement of core components will be completed, the price of terminal industrial embodied robots will drop to 100,000 yuan, the penetration rate of core scenarios in the discrete manufacturing industry will exceed 5%, and it will gradually cover about 80% of single simple industrial processes, becoming a core supporting technology to solve the difficulty of recruiting workers in the manufacturing industry and improve production efficiency.
