How Korea's Tech Giants Are Betting Big on Robotics and AI

South Korea's largest manufacturers—Hyundai, LG, and Samsung—are making major investments to become key suppliers of the robots and computing systems that factories will need as they increasingly adopt AI and autonomous technology. The move builds on decades of experience in precision manufacturing, but it represents a significant shift in focus for companies that have traditionally made cars and consumer electronics.

The opportunity exists because factories worldwide are under pressure to integrate robots and AI-powered quality control into their operations. That creates demand for specialized hardware and software tailored to industrial use—demand that these Korean companies are positioned to fill.

Hyundai's Move Into Industrial Robotics

Hyundai established its Robotics Lab in 2019 and acquired Boston Dynamics in 2021, the robotics research company known for its advanced four-legged robots. But Hyundai's ambitions go beyond showcasing cutting-edge machines. At a major robotics conference in early 2025, the company unveiled MobED, a mobile robot platform built to work in real factory environments—moving materials, handling tasks, and navigating complex spaces on factory floors.

What makes MobED noteworthy is a technical improvement: its motor system can boost power output by up to 70 percent compared to existing designs. In practical terms, that means the robot can work longer on a single charge and carry heavier loads without sacrificing precision. For factory operators, that translates to fewer recharge cycles and less downtime.

Hyundai's strategy is to treat its own factories as test beds. Engineers deploy experimental robots on actual manufacturing lines to work out real-world problems—navigation around obstacles, coordination with human workers, consistent performance under factory conditions—before selling refined versions to other manufacturers.

LG's Smart Factory Platform

LG Electronics announced in mid-2024 that it would expand its smart factory solutions business, combining artificial intelligence, digital tracking systems, and its six decades of experience building complex production lines. The offering covers system design, real-time monitoring using a technique called Digital Twin (essentially a virtual replica of a physical factory that engineers can monitor and adjust), and AI-powered checks for quality control and equipment maintenance.

LG positions itself as a systems integrator—meaning it supplies not just individual robots but the software and management tools to tie them all together. The company applies lessons learned from its own consumer electronics manufacturing directly to these customer solutions. This approach reduces risk because LG can test new quality-control systems on its own production lines before selling them to external customers.

The Computing Power Behind the Robots

All these robots and AI systems require significant computing power. Consider one example: Cerebras Systems, a semiconductor company, recently announced a processor with 2.6 trillion transistors and 850,000 specialized cores designed to accelerate artificial intelligence tasks. That is a substantial leap forward in capacity—the company's previous chip, released in 2019, had only 400,000 cores.

To put that in perspective, more cores mean the processor can handle more calculations simultaneously, which matters when a factory robot needs to process sensor data (vision, touch, distance) in real time to make split-second decisions about movement or manipulation.

Nvidia, the dominant player in AI computing hardware, continues to release more powerful processors for this exact purpose. The combination of more capable chips and better software allows robots to become faster, smarter, and more autonomous.

Why Korean Manufacturers Are Positioned to Win

This pattern has appeared before in technology. In the 1990s, personal computer makers expanded into servers as companies began buying networked computers. Mobile phone manufacturers moved into chip design when smartphones demanded custom processors. Korean companies are now following a similar playbook: control as much of the robotics stack as possible, from chip design to the robots themselves, to capture more profit and reduce dependence on outside suppliers.

Samsung offers a precedent. In 2016, the company spent $8 billion to acquire Harman, a supplier of automotive electronics. That gave Samsung expertise in building tough, reliable components for vehicles—knowledge now useful in industrial robots that must work reliably in harsh factory environments.

One competitive reality to acknowledge: Taiwan Semiconductor Manufacturing Company continues to lead in the ability to manufacture the most advanced chips at scale. However, a recent data breach at TSMC—confirmed after the company was targeted by a major ransomware gang—illustrated a vulnerability in global semiconductor supply chains that could incentivize companies to seek alternative suppliers or build redundancy.

Academic Partnerships Accelerate Development

Korean manufacturers are also partnering with universities to speed up research and prototyping. Pusan National University, for example, hosts a research center (the Rolls-Royce University Technology Center, established in 2008) that brings together academic researchers and industry engineers. Universities provide access to specialized equipment and talented graduates; manufacturers provide real-world problems and the resources to solve them at scale.

The Infrastructure Investment Ahead

Shifting a factory to use robots and AI requires significant capital. Factories need computing systems at the edge—small data centers inside the factory itself—to make split-second decisions without relying on distant cloud servers. At the same time, the factory must stay connected to cloud systems where companies train and update AI models.

Network connectivity becomes critical. Factories deploying many connected robots and sensors need fast, reliable communication with minimal delay. This is why some manufacturers are building private 5G networks within factories—to ensure the speed and reliability that safety-critical systems demand.

The broader context here is that Korean manufacturers are not simply adopting robotics as users; they are positioning themselves to become the suppliers that other factories depend on. If this strategy succeeds, it could reshape which companies control the supply chains for robotics components and AI hardware globally. The outcome also depends on how quickly these companies can execute and whether they can maintain quality as they integrate increasingly complex autonomous systems into their own manufacturing operations.

Korean manufacturers have built strong track records in scaling advanced manufacturing processes at high volumes, which suggests reasonable prospects for success. Whether they can move fast enough to capture market share before other competitors move in will depend on the next few years of execution.