Samsung Electronics has secured roles in South Korea’s Hyper AI Network program. The company signed contracts with KT and SK Telecom for industrial AI-RAN trials. The projects will test private 5G networks, edge AI, and robots in demanding workplaces.
However, this is not a commercial AI-RAN launch. It is a supplier selection and deployment phase. Field pilots should begin in October 2026. The two-year program has government backing through South Korea’s science and ICT authorities.
The program carries about KRW 17.2 billion in total funding. That equals roughly $12.7 million. The budget shows a clear focus on validation. It does not suggest nationwide network replacement or mass commercial rollout.
A key goal is to test “physical AI” in real industrial settings. This means AI inside machines that sense, decide, and act. Examples include robots, autonomous vehicles, and inspection systems.
The trials will focus on predictable uplink performance and low latency. They will also test reliability, local processing, and automated network operations. These needs differ greatly from consumer mobile broadband. A shipyard or petrochemical plant needs stable control, not headline download speeds.
KT will run its project at HD Hyundai Samho’s Yeongam shipyard. Planned use cases include welding robots and AI-assisted painting robots. KT also plans autonomous robots for telecom facility checks. Samsung will supply its Network in a Server platform for this deployment.
That platform places key network and AI functions on site. It combines virtualized RAN, an AI core, and AI applications. Samsung will also provide CognitiV Network Operations Suite. The suite helps manage and automate the private 5G environment.
Meanwhile, SK Telecom will test AI-RAN at SK Incheon Petrochem. Its first use case involves an autonomous patrol robot. The robot will stream high-definition video from hazardous areas. AI systems will then analyze those feeds for possible risks.
SK Telecom is taking a broader vendor comparison approach. It plans to evaluate Samsung, HFR, Ericsson, and Nokia equipment. This could give the industry useful data. It may show how different architectures perform under real pressure.
The trials matter because industrial networks create different traffic patterns. Robots, cameras, and LiDAR sensors send heavy upstream data. These systems also demand predictable response times. Standard mobile-network trials rarely expose those operational stresses.
Still, major questions remain. Vendor claims about ultra-low latency need independent field results. Robot safety also depends on more than connectivity. Design, sensors, certification, and human oversight remain essential.
The projects also add complexity. Edge compute, automation software, and AI workloads increase operational demands. Industrial operators will need clear returns. Safety gains, productivity improvements, and lower operating costs must justify the investment.
For Samsung, the program offers a strong domestic proving ground. It can test private 5G, edge AI, and automation together. For South Korea, the work supports its longer-term “AI-native 6G” ambition. Yet the actual pilots still run on today’s 5G Standalone technology.
The next milestones will be practical. Engineers will watch latency variation, uplink throughput, and robot task completion. SK Telecom’s vendor comparisons may prove especially valuable. If the results hold, AI-RAN could move beyond slogans and into factories.
