Korea Electronics Association: AI Vision Inspection Replaces Manual Checks, But Industry Adoption Remains at 11.7%
A Korea Electronics Association report shows AI significantly improves efficiency in manufacturing QC and R&D, but overall adoption remains low due to data integration and training challenges.
The Korea Electronics Association (KEA) released its 'AI Utilization and Job Changes in the Electronics Industry Field' report on November 8, 2026, detailing specific applications of artificial intelligence in South Korea's electronics manufacturing sector and their impact on workflows. While AI demonstrates significant potential in enhancing production efficiency and shortening development cycles, overall industry adoption remains in the early stages.
The report highlights that a domestic manufacturer supplying refrigerator doors to major home appliance companies (referred to as Company A) implemented an AI vision inspection system. This system captures images of the four corners of refrigerator doors via cameras and uses AI to determine defects, replacing two previous manual visual inspectors who were reassigned to other processes. The role of quality management personnel also shifted from direct product inspection to verifying AI judgments and handling exceptions. However, the implementation revealed new challenges: whenever product models or specifications changed, camera positions and inspection criteria had to be adjusted, and additional training data was required. Ensuring data accuracy between the AI system and existing production management systems also became critical.
In the R&D phase, another home appliance control device developer (Company B) used AI to assist in circuit design and component selection, reducing the product development cycle from approximately three months to three weeks to one month. Additionally, an electronic device development and manufacturing company (Company C) automated code writing and review using AI, lowering the proportion of manually written code by developers to less than 10%. These cases indicate that AI is changing the nature of repetitive work, increasing the demand for advanced skills such as condition setting, verification, and exception handling.