# How far are robots from actually working on production lines? Galbot’s path to industrial AI > Source: > Published: 2026-08-27 02:06:41+00:00 For decades, industrial robots have primarily been used to handle repetitive labor. On highly standardized production lines such as automotive manufacturing and electronics assembly, robotic arms have become a core part of factory automation thanks to their precision and reliability. However, as manufacturing moves toward greater flexibility and intelligence, companies are demanding more from robots: not only the ability to perform fixed movements, but also the capacity to adapt to complex environments and handle less standardized tasks. This shift has become a key driver behind the exploration of embodied AI robots in industrial settings. Galbot, a Chinese embodied AI robotics company, is exploring industrial applications under this trend. The company aims to accelerate the transition of robots from laboratories into real-world production environments by integrating robotic hardware, intelligent models, and data systems. Founded in May 2023, Galbot has attracted major attention from investors as the embodied AI sector gains momentum. The company completed multiple rounds of financing, raising more than RMB 2.4 billion ($360 million) in total funding by 2025, including an RMB 1.1 billion ($160 million) financing round announced in June 2025. In 2026, Galbot announced another RMB 2.5 billion ($370 million) financing round, with investors including the National Artificial Intelligence Industry Investment Fund, Sinopec, and CITIC Investment Holdings. The company’s valuation has reportedly exceeded RMB 22 billion ($3.27 billion). Galbot G1 is one of the company’s representative products. The robot combines a mobile platform with a dual-arm manipulation system, overcoming the limitations of traditional industrial robotic arms that are fixed to specific workstations. With greater mobility, G1 is designed to perform tasks such as picking, transporting, and organizing objects across different environments. Compared with stationary robotic arms, mobile manipulation robots offer greater flexibility. Traditional industrial robots are usually installed at designated positions and perform predefined workflows, while mobile robots can adjust their locations and actions based on different tasks, making them more suitable for future flexible manufacturing scenarios. For manufacturers, this type of robot has strong application potential. Many production processes still rely heavily on human workers for tasks such as material handling, sorting, and loading or unloading components. These jobs are often repetitive but require adaptation to different objects and changing conditions. Traditional automation solutions struggle to fully cover these scenarios, which creates an opportunity for embodied AI robots. Beyond G1, Galbot has also introduced Galbot S1, a robot designed specifically for industrial environments. Compared with robots targeting general service scenarios, S1 focuses more on manufacturing tasks such as transportation, palletizing, and machine loading, and it aims to help companies address repetitive, labor-intensive operations and rising labor costs. Industrial applications are widely viewed as a major pathway toward the commercialization of embodied AI robots. On one hand, manufacturing provides clear demand, as companies seek automation upgrades to improve efficiency. On the other hand, compared with open environments such as homes, factories are more structured, making them better suited for long-term robot operation and data accumulation. However, bringing robots into factories is not simply about replacing human workers. Instead, it represents a potential transformation of production methods. In the future, robots may increasingly take on high-intensity, repetitive, and hazardous tasks, while working alongside human employees to improve productivity and safety. A key factor behind industrial adoption will be the advancement of AI capabilities. Traditional robots mainly depend on engineers to manually program every movement. Embodied AI robots, however, require stronger abilities in understanding, planning, and learning. Galbot’s AstraBrain embodied intelligence system is designed to combine visual perception, task planning, and motion control for better robot interpretation of instructions and adaptation to environmental changes. This represents a shift from robots simply executing predefined commands to robots gradually gaining the ability to handle more complex tasks. Still, the industrialization of embodied AI robots remains at an early stage. Challenges including cost, reliability, stability, and large-scale deployment continue to limit wider adoption. For robotics companies, the real challenge is not demonstrating a robot completing a single task, but proving that robots can operate continuously in real production environments and generate measurable economic value. As AI continues to merge with robotics, industrial scenarios are emerging as a critical gateway for embodied AI commercialization. For Galbot, being able to move is only the first step. The real test is whether robots can actually work and create value in the industry. In the future, robots that can enter manufacturing environments and solve practical production challenges may play an increasingly important role in the next wave of industrial intelligence upgrades.