LG CNS is making a push into the “Physical AI” market, which merges the real world and AI, including robots, as a core strategy for 2025.

LG CNS aims to upgrade robots into entities that can do real work on site, based on its years of experience in manufacturing and logistics, along with its AI and systems integration capabilities.

CEO Shin-kyun Hyun said, “LG CNS fine-tunes robot hardware with the various industrial-site data the company holds and works to create robots that can operate in real sites.” He said training robots deployed on site, monitoring whether they are doing their jobs well, and retraining them are critical processes. He said that role will be key to deploying robots in industrial sites.

The company said South Korea is considered a suitable market to verify and advance Physical AI because the country has a high share of manufacturing based on diverse industries and many processes that require skilled work.

Hyun said, “LG CNS is quickly securing Physical AI technology and applying it on site based on the South Korean market, which centers on manufacturing, and is securing a competitive edge.” He said LG CNS, which knows industrial sites best, will lead the Physical AI market.

For its Physical AI strategy, LG CNS stresses “Maestro,” which designs and coordinates an overall system so that different robots, from different makers and for different purposes, can move as a team rather than as individual robots.

To that end, LG CNS carries out the entire process from robot training to testing and verification. The company said understanding how real work proceeds at a site matters above all because manufacturing and logistics sites differ in roles and work methods by process.

Hyun said, “LG CNS has built a high level of understanding of ‘how certain work is carried out’ and ‘what judgments and know-how are needed at each stage of work’ through experience across a range of industrial sites.” He said the company trains robots on how they should work on site by comprehensively considering process characteristics, difficulty and workflows by industry, and is evolving them to develop “industrial intelligence” that understands the language and rules of the field.

LG CNS is also preparing to build a data platform that enables robots to continuously learn from on-site data. Its plan is to upgrade robots so they can adapt on their own and perform precise tasks even as environments and work conditions change from moment to moment.

LG CNS is expanding its Physical AI strategy into the robot hardware area as well. It is speeding up demonstrations so industrial “humanoid robots” can be used at sites such as smart factories and smart logistics.

It is currently conducting proof-of-concept projects at factories and logistics centers of about 10 customers. In shipbuilding, it is pursuing PoCs for humanoid robots that inspect whether each ship part has been properly assembled. In logistics centers, it is pursuing PoCs for humanoid robots that can carry out tasks such as stacking boxes or collecting empty boxes.

LG CNS is focusing in particular on automating high-value work that has been difficult for robots to perform. Its goal is to raise productivity and safety at the same time by deploying humanoid robots in processes that require split-second decisions, where tasks change frequently, or that pose safety risks and have placed heavy burdens on people.