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HD Hyundai Robotics presented the results of its Physical AI collaboration as a keynote speaker at Palantir’s “Sovereignty Bootcamp” in New York. The two companies applied AI agents to robot programming, cutting problem-solving time by about 63%, from an average of 21.5 days to 7.9 days, and expect to reduce robot programming costs by more than 50%. Field engineers are being repositioned as specialists who define problems and implement solutions, and the two companies plan to hold regular steering committee meetings to broaden the scope of their collaboration.
Key Elements
HD Hyundai Robotics has disclosed the results of its Physical AI collaboration with U.S. AI software company Palantir Technologies. The key takeaway: by deploying AI agents in robot programming, the companies cut problem-solving time by more than 60%.
HD Hyundai Robotics said on the 1st that Ahn Sung-hwan, its chief technology officer (CTO and executive director), attended Palantir’s “Sovereignty Bootcamp” in New York recently as a keynote speaker and presented the status of the two companies’ collaboration and cases of on-site application. The event, which discusses ways to strengthen AI competitiveness while protecting companies’ core data, has drawn more than 450 executives from some 250 global institutions and companies across its three sessions since it was first held in July.
The collaboration focuses on changing the way robots
The collaboration focuses on changing the way robots are programmed on industrial sites. Previously, skilled engineers had to repeatedly adjust work sequences, travel paths and speeds while visually checking robot movements. Because the structure relied on individual experience, there were limits to standardizing tasks and securing efficiency. To improve this, the companies introduced a method in which AI agents first analyze existing robot programs and propose improvements, and engineers then review and refine them based on field experience.
The actual results have been confirmed since August. Applying AI agents to the problem-solving process reduced the average task period from 21.5 days to 7.9 days, a drop of about 63%. HD Hyundai Robotics expects this workflow innovation to cut robot programming costs by more than 50% as well.
| Category | Previous method | After applying AI agents |
|---|---|---|
| Average problem-solving period | 21.5 days | 7.9 days (about 63% shorter) |
| Robot programming cost | Baseline | Expected to fall by more than 50% |
| Engineer’s role | Repeatedly adjusting paths and speeds directly | Defining problems and implementing solutions |
Note: Pilot application results disclosed by HD Hyundai Robotics
The role of field engineers is also being redefined. The company plans to move them away from a focus on robot programming, installation and commissioning and cultivate them as “field solution specialists” who define on-site problems themselves and implement solutions using AI technology.
The two companies plan to hold regular steering
The two companies plan to hold regular steering committee meetings involving key executives to set priorities for joint tasks and continue identifying new cases of Physical AI use. “We are continuing to expand cooperation with global companies to further advance our Physical AI capabilities,” Ahn said. “We plan to identify tasks that can solve on-site problems faster and more effectively and expand the scope of application for our Physical AI solution business.”
The case is drawing attention for presenting a model in which a robot manufacturer goes beyond its own hardware and combines it with a software company’s AI capabilities to raise productivity on industrial sites. Some observers say that if it can lower the burden of programming and commissioning costs—long cited as an obstacle to robot adoption—it could also spur greater automation investment at manufacturing and logistics sites. However, specific savings figures and additional application sites have not yet been disclosed, so it remains to be seen how far the results will extend into actual business scope.
