[Editorial] The AI-driven transformation into 'Beyond Semiconductors' must not end as a slogan

The government on the 6th unveiled a blueprint for economic structural reform aimed at lifting the country’s potential growth rate. At the center of the plan is a 'Beyond Semiconductors' strategy that seeks to spread growth engines beyond semiconductors to key industries such as steel, petrochemicals, shipbuilding, automobiles and biotechnology. The plan calls for introducing Artificial Intelligence (AI)-based manufacturing processes and hydrogen reduction steelmaking in the steel industry, while petrochemicals will pursue AI-driven process innovation and business restructuring. In shipbuilding, humanoid robots such as welding robots will be deployed, and in automobiles, AI Factory systems and autonomous driving technologies will be expanded. The government also announced plans to develop robots tailored to the 10 major industries and supply 1,000 AI robots annually.
The direction is right. The Korean economy is highly dependent on the semiconductor cycle, which causes exports and growth to swing sharply, and it must move beyond that structure. With the working-age population shrinking and investment remaining sluggish, potential growth continues to decline, and manufacturing productivity must be raised. AI can be a useful tool for that task. Given Korea’s strong manufacturing base and rich process data, the country can expect greater synergy by applying AI directly on production sites. It is also a meaningful strategy for securing leadership in Physical AI, the next major battleground in the AI industry.
But simply adding AI does not suddenly turn industries that are losing competitiveness into growth engines. Petrochemicals, in particular, urgently need capacity reductions and business restructuring because of oversupply from China. Steel faces a triple burden: China’s low-price offensive, soaring carbon-transition costs, and rising protectionist barriers around the world. The automobile industry is also confronting major challenges as the industrial order shifts rapidly toward electric vehicles. If AI transformation is rushed while inefficient facilities and uncompetitive businesses are left untouched, restructuring will be delayed and only the lifespan of weak companies will be extended.
The government must make its industry-by-industry restructuring principles clear and redraw the timetable for reform. Its ongoing efforts to reorganize key industries are moving too slowly, and the support measures still have many gaps. In petrochemicals, reducing excess capacity in some regions is worth acknowledging, but the results remain unsatisfactory. The steel industry is even worse. Restructuring is dragging on endlessly. The government needs to present a concrete plan for capacity cuts and for support in low-carbon, high-value-added production. The auto industry also needs a comprehensive roadmap that includes retraining and redeploying workers for the transition to future mobility vehicles.
Policy inconsistencies must also be corrected. While the government is calling for 'Beyond Semiconductors,' it excluded electric vehicles, low-carbon steel and recycled plastics from the production tax credit program, often described as a 'Korean-style IRA.' In other words, it is offering tax incentives to encourage domestic production in semiconductors, rechargeable batteries and AI robot components, while leaving out traditional core industries. Limited fiscal resources cannot support every industry. But if the government is restructuring crisis-hit core industries into high-value AI sectors while excluding them from tax support needed to preserve production bases, its policy consistency will inevitably be questioned.
Targets such as training 200,000 AI specialists or creating 200,000 youth jobs should also not become exercises in meeting numbers for their own sake. In the past, governments have often set job creation and workforce training targets, only to fall short because they were disconnected from actual demand in industry. What matters is whether universities and vocational training institutions can properly train the workers companies need. Education and labor market systems must also be overhauled so that existing manufacturing workers can move into new jobs during the AI transition. If 'Beyond Semiconductors' is not to end as a slogan, the country will need patience and persistence to change the very structure of its industries.