• Date: November 13th, Friday, 2026, 17:00 – 18:30
• Location: Room 304, SNUAC (Bldg. 101)

Presenter: Suk-bum Hong (Director, KMWU Labor Research Center)

This study explores the current state of physical AI adoption and its associated challenges in manufacturing workplaces through case studies of seven workplaces within the automotive supply chain. It begins from the observation that public discourse surrounding physical AI has been disproportionately focused on when humanoid robots will be deployed on production floors and whether they will replace human labor. Defining physical AI broadly as a component of smart manufacturing process innovation, the study examines four categories of technologies in automotive manufacturing: production process automation, logistics and material handling automation, physical AI in the narrower sense, and digital production management and control. The findings reveal that the technological infrastructure of automotive manufacturing currently consists primarily of a combination of conventional production process automation and digital production management centered on manufacturing execution systems (MES), while physical AI in the narrower sense has either not yet been introduced or remains at the pilot stage. The most widely adopted smart manufacturing technologies are not those that directly replace manual labor, but rather advanced digital technologies that integrate the entire supply chain into a unified production flow. The extent and manner of technology adoption vary according to factors such as the products being manufactured, production methods, workers’ employment status within the workplace, firms’ positions within the supply chain and their corporate governance structures, and the bargaining power of labor unions. These findings demonstrate that the effects of technology do not follow directly from its design principles but instead emerge unevenly along the existing social order and hierarchical structures in which it is embedded. They also show that the risks associated with introducing new technologies are disproportionately concentrated among firms at the lower tiers of the supply chain and workers in precarious employment. This suggests that responding to the technological paradigm shift driven by physical AI requires institutionalizing participation and accountability across the supply chain, moving beyond employment protection at the individual workplace level.

Keywords: Automotive Industry Process Innovation; Physical AI; Smart Manufacturing; Prime Contractor–Subcontractor Relations; Social Embeddedness of Technology