Recently, the General Office of the Ministry of Industry and Information Technology and the General Office of the State owned Assets Supervision and Administration Commission of the State Council jointly issued a notice on the joint implementation of the 2026 special action for real-life training of humanoid robots and embodied intelligence. The goal is to promote the transformation of humanoid robots and embodied intelligence from "performance mode" to "operation mode" through real-life training.

The demonstration and verification demonstrate the technical limit, single point capability, and ornamental value, and prove that it can be achieved; Normalized operations require stability, durability, continuous operation, and reasonable cost, and must demonstrate the ability to consistently achieve and do well. Currently, embodied intelligence is standing at this watershed, moving from the laboratory to real scenes, and from "performance mode" to "homework mode".

The policy countdown has started,The real exam question for the industry has just begun: what does' real work 'mean?

The three hard indicators of 'real work': understanding the scenario, understanding the boundaries, and understanding the integration

The narrative of embodied intelligence in the past few years has been largely dominated by "demo economics". A robot completes one capture and walks a certain distance, with millions of video views, but it is far from the "scale of tens of thousands of units".

Where is the problem?Performance and homework do not test the same set of abilities.

'Real work' requires three prerequisites to be met simultaneously: understanding the scene, understanding the characteristics and capability boundaries of the robot, and being able to form an integrated solution.

Understanding the scene is to penetrate the simplified conditions of the laboratory, see the dynamic variables in the real world, make the solution grow in the scene, and based on this, enable the robot to make adaptive solutions.Behind this is a profound understanding of the needs of different industries, a continuous cultivation of long-term dimensions, and the repeated accumulation of massive data。

Understanding the boundary of robot capabilities isUnderstand what each type of robot can and cannot achieve, know which tasks can be autonomously closed loop, and what requires collaborative supportWe neither equate laboratory highlight performance with mass production delivery capability, nor deny the path due to temporary inability to achieve it.

Is it possible to form an integrated solutionEnable different types of robots to work together and showcase their strengths, while integrating software and hardware resources and data links，Form a collaborative, schedulable, and scalable system delivery,Instead of isolated stacking of single point technologies.

Warehousing: a 'golden place' with embodied intelligence

If "understanding the scene, understanding the boundaries, and understanding integration" are the three rulers to measure whether a robot can "really work", thenWarehouse logistics is undoubtedly the most suitable inspection site at present。

The task boundaries here are clear, the variables are centralized and controllable, but there are also real tests of the system's capabilities from complex working conditions - both the accuracy requirements for identifying and capturing massive SKUs, and the extreme pressure for collaboration and stability from large-scale scheduling.

That's why,Warehousing is rapidly becoming a "golden place" for top robotics companies around the world to flock in。

Figure、Agility、 Tesla Optimus has announced warehouse testing successively; Apptronik collaborates with GXO Logistics to promote warehouse picking; At the release of G1, domestic Yushu Technology also clearly positioned it as targeting industrial manufacturing and logistics warehousing scenarios.

Giants are pushing warehouse robots from concept testing to large-scale deployment - and as competition crosses the threshold of 'who can do it' and enters a new stage of 'who can deliver at scale',The depth of scenes and ecological network accumulated by the pioneers over the years actually constitute a moat that is difficult for latecomers to cross in the short term。

Using a three-tier architecture, answer the question of 'real work'

When the industry verifies the strategic value of warehousing scenarios, a natural question arises: Who runs the farthest and accumulates the deepest on this track?

According to the 2025 Mobile Robot Market Report by the global market research firm Interact Analysis, Jizhijia has been ranked first in the global autonomous mobile robot (AMR) market share for seven consecutive years. More noteworthy is the structural leading advantage - in the global warehousing fulfillment market, the company has a market share of 23%, which is approximately the sum of the second and third place market shares. At the same time, the company maintains a leading position in core overseas regions such as EMEA, APAC, and the United States.

Behind the market position is the continuous realization of large-scale delivery capabilities. By the end of 2025, Jizhijia has shipped over 72000 robots to more than 40 countries and regions worldwide, serving approximately 950 end customers, including over 80 Forbes 500 customers worldwide, with a repeat purchase rate of approximately 78% for major customers.

Behind the leading scale is Jizhijia's continuous cultivation of the three abilities of "understanding scenarios, understanding boundaries, and understanding integration".

Understand The SceneBeing the world's number one in seven years is not just a time scale, but also an accumulation of scene density. Jizhijia serves approximately 950 end customers, covering multiple industries such as retail, footwear, e-commerce, 3PL, automotive, pharmaceuticals, and lithium batteries. Each industry has its own unique warehousing logic, SKU characteristics, and operational pace.

This cross industry and large-scale delivery experience has enabled the company to accumulate a complete set of capabilities from "seeing problems clearly" to "adapting solutions" - this scenario know-how is a barrier that latecomers cannot overcome in the short term through funding and talent introduction.

Know The BoundariesJizhijia has a clear judgment on the capability boundaries of robots, and each type of product has its own responsibilities, building a complete capability echelon.

Among WhichAMRResponsible for standardized high-frequency processes such as handling and storage, specialized equipment has the highest efficiency and is the basic foundation accumulated by Jizhijia over the past decade.Unmanned Picking WorkstationWe have overcome the technical challenges of precise picking and efficient adaptation when facing large-scale product SKUs, covering tens of thousands of products and effectively dealing with complex categories such as irregular parts and flexible packaging, achieving true unmanned picking across multiple categories, scenarios, and industries.

And the upcoming World Artificial Intelligence Conference will make its debutGino 1， Specially designed for warehousing, its embodied brain Geek+Brain deeply integrates the massive warehousing data accumulated by Jizhijia over the past decade. Equipped with humanoid full joint force control arms and three finger dexterous hands, it can engage in multi task operations such as picking, moving boxes, packaging, and inspection, truly achieving "one robot covering mainstream manual operation scenarios in the warehouse" and flexibly filling the flexible gap.

Understand IntegrationAfter the boundaries are clear, it is even more crucial to enable efficient collaboration among different robot solutions. Jizhijia's integrated software system can command different robots in the warehouse and provide customers withTailored intelligent overall solutionTransforming the process of humanoid robots entering warehouses from "single point upgrade" to "system delivery" significantly accelerates the pace of commercialization.

The three abilities are interrelated - scenario accumulation allows Jizhijia to know what customers really need, boundary judgment allows the company to understand what each type of product should do, and system integration allows different abilities to collaborate efficiently on the same platform. These are exactly the three thresholds that embodied intelligence needs to cross from "demo" to "real work in the warehouse".

Moreover, the customer resource advantage of Jizhijia enables faster implementation of embodied intelligent business: customers propose real needs, provide real data on site, and feedback drives product iteration - this "scenario data technology" closed-loop system enables every technological breakthrough to find validation scenarios in the shortest possible time, naturally shortening the path from release to large-scale replication.

This is the "real work" answer sheet submitted by Jizhijia.