[Yongchun Kim (김용춘), head of Avnet Korea] Dramatic advances in artificial intelligence are shaking the foundations of manufacturing worldwide, shifting the focus from simple output to precision, complexity and adaptability. This paradigm shift is especially important for South Korea, which already leads globally in industrial automation. South Korea has reached a point where it must push more aggressively to adopt AI to protect its competitive edge in core industries such as semiconductors, electronics and automobiles.
◆Why automation is imperative for South Korea: a strategic necessity
While global manufacturing trends emphasise fast assembly lines, automation in South Korea is a strategic necessity accelerated by demographic factors. South Korea already ranks among the world’s highest in robot density, measured as robots per 10,000 workers, posting 1,012 as of 2023. (Source: International Federation of Robotics (IFR), World Robotics 2024 report). This high concentration of automation is a key tool for responding to a shrinking working-age population.
The domestic AI robot market is forecast to grow to about 1,874,650,000 dollars by 2033, helped by the government’s 'Manufacturing AI Transformation (M.AX)' policy. (Source: Straits Research, South Korea Industrial Robots Market report). Supporting this, South Korea’s AI-in-manufacturing market is predicted to grow explosively with a compound annual growth rate of 52 percent from 2025 to 2030. (Source: Grand View Research, South Korea Artificial Intelligence in Manufacturing Market report). This shows how quickly South Korean companies are integrating cognitive capabilities into core production processes.
◆Machine vision: the 'sharp eye' of ultra-precision manufacturing
In South Korea’s highly specialised electronics and semiconductor plants, quality inspection directly affects profitability. AI-based machine vision systems serve as the 'sharp eye' essential for ultra-precision work. This next-generation machine vision has achieved technological innovation by combining 3D visual perception, point-cloud processing and large vision models.
Image sensors, a core component of any machine vision system, have a huge impact on product performance, but there is no one-size-fits-all solution. This technical insight underscores that sophisticated hardware choices are essential for reliable AI implementation. High-precision RGB-D cameras enable millimetre-level positioning. Dynamic object-recognition algorithms can also handle workpieces piled up in disorder. Large vision models achieve accuracy of 99.9 percent or more with limited samples, transforming quality inspection into an instant digital task.
◆Smart decision-making: from simple execution to autonomous optimisation
If vision systems provide robots with 'eyes', AI decision engines provide the 'brain'. In South Korea’s advanced automotive assembly plants, managing flexible mixed-flow production, where a single line handles multiple models, requires a complete smart closed-loop system. The most revolutionary development here is the introduction of zero-shot learning capability through large industrial models.
This makes it possible to identify general objects without registration, allowing robots to adapt quickly to new parts without extensive reprogramming. This is a core value of the future fully automated 'lights-out factory', sharply cutting production line changeover time.
◆Embodied intelligence: an 'eye-brain-hand' system for collaboration
Emerging embodied AI technology frees conventional industrial robots from dependence on structured environments. An integrated 'eye-brain-hand' platform using multimodal cognition enables robots to understand and interact with their surroundings using visual data alone. This closed-loop model is rapidly expanding beyond manufacturing sites. In South Korea’s growing e-commerce logistics sector, 3D vision acts as 'smart eyes', precisely guiding robots to efficiently sort packaging materials of various shapes and sizes.
At least 240 new technologies are expected to emerge across a broad smart-solution landscape by 2030. It is important for the industry to support this growing trend by providing innovative smart solutions to South Korea’s fast-growing market through proprietary ecosystems and end-to-end IoT service portfolios. This means focusing on supplying the components and integration expertise required for complex AI applications, whether in logistics or ultra-precision manufacturing.
◆Overcoming future challenges for AI and robotics in South Korea
South Korea is in the lead, but it faces unique challenges in scaling AI adoption. A 2024 survey by the Korea Federation of SMEs (KBIZ) found the main obstacles keeping domestic manufacturers from adopting robots were the burden of upfront costs at 44.2 percent and a lack of specialist personnel at 20.5 percent. (Source: Straits Research, citing the KBIZ survey). If the benefits of AI adoption are concentrated in large companies with mature capabilities, the productivity gap between large firms and small and medium-sized enterprises could widen.
To resolve these fundamental challenges, accessible, integrated solutions are essential in addition to capital investment. A focus on platform simplification and specialist hardware supply is the foundation for reliable AI systems in South Korea’s demanding manufacturing environment.