The semiconductor boom is leading to large-scale bonuses and expanded investments, while traditional manufacturing sectors are struggling to secure the resources necessary for future growth. This has intensified the concentration of capital and talent. Experts are urging immediate government support for industries such as automotive, petrochemicals, and steel to innovate productivity through artificial intelligence (AI).
According to the Bank of Korea on October 29, the total bonuses for major industries, including semiconductors, automotive, and shipbuilding, are projected to reach up to 70 trillion won next year, a 6.4-fold increase from this year's 10.9 trillion won. Notably, bonuses for Samsung Electronics and SK Hynix alone are expected to be around 60 trillion won, widening the wage gap between sectors.
The expectations for growth and compensation in various sectors are influencing the career choices of engineering graduates. The number of applicants for semiconductor contract departments at five universities—Yonsei University, Korea University, Sogang University, Sungkyunkwan University, and Hanyang University—for the 2027 academic year has reached 5,992, a 19.4% increase from the previous year, marking a record high. The competition ratio stands at 28.53 to 1.
In contrast, the number of applicants for the battery department at Sungkyunkwan University, linked to Samsung SDI, has decreased by 117 (36.2%) compared to last year, while applicants for contract departments in telecommunications and mobile fields have also dropped by 11.0% and 21.3%, respectively. Despite a general preference for contract departments due to job market challenges, the trends vary by field.
Expectations surrounding AI are also reflected in corporate investment strategies. Traditional manufacturers are actively investing in businesses linked to AI demand. LG Electronics plans to invest an additional 220 billion won to enhance production capabilities and upgrade domestic and international production sites in response to the demand for AI data center cooling solutions. Doosan Enerbility aims to increase its large gas turbine production capacity at its Changwon facility from eight units annually to twelve by 2028, in line with the growing demand for power generation equipment due to the expansion of data centers.
Experts advise that to broaden the growth momentum concentrated in semiconductors to traditional manufacturing, AI must be integrated with existing manufacturing capabilities to enhance profitability. A downturn in the industry could stifle investment and talent acquisition, delaying technological transitions and solidifying competitive gaps between sectors. AI can be utilized in automotive product development and quality inspection, as well as in process control and energy optimization in steel and petrochemical industries, to reduce costs and enhance the competitiveness of high-value products.
However, relying solely on AI transformation (AX) will not resolve issues of weak demand and oversupply. There is a need for government-level regulatory easing and institutional reforms to support research and development and the upgrading of facilities while facilitating a shift toward high-value product-focused business models. As capital and talent migrate to growing industries, it is crucial for traditional manufacturing to secure new revenue sources and create conditions for reinvestment.
Kim Dae-jong, a professor at Sejong University, stated, "It is natural for capital and talent to move to more profitable industries, but if competitive companies collapse during the industrial transition, it will result in a loss for the entire national economy. The government needs to actively support the productivity enhancement of struggling industries to help them regain competitiveness."
* This article has been translated by AI.
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