Hwang Myeon-jung (황면중), a professor at the University of Seoul, said the core of physical AI, including robotics AI, is hardware stability and reliable operation. He said robotics AI capability depends on perception and manipulation, and his team focuses research on improving speed and accuracy. His lab won the RoboCup 2026 ARM Challenge, sorting dozens of items in 30 minutes with near-perfect accuracy. He said manufacturing sites are a key commercialization target.

As agentic AI moves beyond support to execute tasks inside workflows, trust becomes unavoidable. The risk comes less from AI acting alone than from engineering workflows that fail to express system-level behaviour in an executable form. System-first engineering, implemented through model-based design, provides shared, executable system models across mechanical, electrical and software domains. Deterministic, repeatable verification and simulation reduce dependence on hardware testing and allow changes to be assessed early against system-level criteria.