Yoo Choon-sik
Yoo Choon-sik

South Korea’s government is discovering that announcing large investments in artificial intelligence is easier than persuading companies and taxpayers that they will deliver lasting benefits. Recent confusion over the future of its sovereign AI program has exposed uncertainty about how major decisions are made and how success will be measured, a problem that additional spending alone cannot resolve.

Its semiconductor industry provides a strong base for AI development, while dependence on foreign technology in other areas raises legitimate commercial and security concerns.

These advantages and concerns justify a serious national strategy. They do not, however, establish that every government-sponsored model or semiconductor project deserves support, or that the size of an announced investment demonstrates the quality of the thinking behind it.

The recent retreat in enthusiasm for AI investments should prompt the government to reassess whether its plans can withstand less favorable conditions. Although falling share prices should not dictate national technology policy or be taken as proof that AI has lost its economic potential, they highlight the risks of commitments that assume favorable conditions will continue indefinitely.

The government announced its ambition to establish another semiconductor manufacturing hub before securing binding investment commitments from Samsung Electronics and SK hynix. That leaves a considerable gap between a political announcement and an industrial project that companies are prepared to finance.

Semiconductor plants require reliable electricity and water, skilled workers, suppliers and years of preparation, while their commercial prospects depend on the chips they produce and market conditions when production begins. The government can help address infrastructure constraints, but announcing a location and an ambitious investment target cannot eliminate those uncertainties.

Regional development is a legitimate policy objective, but when it influences the choice of a manufacturing site, the government should explain the expected benefits, additional costs and alternatives considered. Without that explanation, even a potentially useful project risks fueling suspicions that electoral considerations took precedence over industrial requirements.

The controversy over domestic AI models raises a similar question about the relationship between policy objectives and the means chosen to achieve them.

After creating uncertainty over the future of the sovereign foundation-model program, officials reaffirmed its continuation while pursuing a separate frontier-model initiative with a proposed allocation of 4.7 trillion won ($3.6 billion) in the 2027 budget request. A commitment of that scale requires a clear explanation of how the two programs fit together.

Science and ICT Minister Bae Kyung-hoon’s argument that rapid technological advances require a more ambitious approach deserves consideration, since research targets cannot remain appropriate indefinitely. Refusing to revise an outdated plan can waste public money just as surely as launching an inadequately examined replacement.

Clearer test of value

But flexibility requires a clear process, with the government explaining which assumptions have changed, what the existing program has achieved, why a separate initiative is needed and how researchers, computing resources and public funding will be allocated between the two programs. Without that explanation, a strategic shift risks appearing to be an attempt to evade accountability for earlier promises.

The terminology itself also requires greater clarity. Describing a new program as a frontier effort says little about the capabilities it will prioritize, the users it will serve or the resources needed to sustain it.

Nor should the existing program be judged solely by whether its participants overtake the largest US developers, as training engineers, building research experience and developing models suited to South Korean users can have value even without global leadership. Those benefits should be weighed against the resources used and the alternatives available.

Domestic ownership and strong results in government evaluations do not guarantee commercial usefulness, as businesses judge models by reliability, operating costs, ease of integration and performance on actual tasks.

The opportunity cost also matters, as funding another general-purpose model leaves less money for computing access for smaller firms, better datasets, research training or the adoption of existing tools. These alternatives may not all be preferable, but a credible spending proposal should show that they were considered and explain why the chosen investment offers greater value.

Security needs may justify public funding for capabilities with limited commercial returns, but the government should explain which dependencies it seeks to reduce, how much domestic control is required and what maintaining those capabilities will cost. National security calls for careful analysis.

A more credible approach to project selection would require the government to publish each program’s purpose, expected costs and supporting evidence before committing substantial additional resources. Independent specialists should review the proposals, while sensitive information can be protected without concealing the rationale for spending.

Funding should be tied to milestones that allow research programs room for experimentation and failure, require commercialization programs and assess security projects for resilience and operational usefulness. A single ranking or headline performance score cannot adequately evaluate all three.

When projects disappoint, continuing support merely because money has already been spent can compound losses, while ending programs without assessing their useful results can destroy capabilities built over years. Decisions to continue, combine, redesign or terminate projects should follow published criteria and preserve knowledge wherever possible.

Because AI development and semiconductor construction extend beyond electoral terms, companies may hesitate to commit if projects depend mainly on the president’s popularity or the preferences of a small circle of officials. Broader scrutiny can strengthen confidence in sound projects and improve their chances of surviving a change of government.

Uncertainty created by abrupt announcements and unexplained revisions imposes delays and costs. Researchers cannot plan confidently, businesses postpone decisions and lawmakers become less willing to defend spending whose purpose remains unclear.

South Korea has good reasons to invest in AI and much to gain, but the government must show how each investment will strengthen the country’s capabilities at an acceptable cost. Its ambition will earn lasting support through decisions that can withstand technological change, commercial disappointment and political scrutiny.

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Yoo Choon-sik

Yoo Choon-sik is a senior AI correspondent covering Korea for MLex Market Insight. He has worked for international media organizations for about 30 years, including as Reuters’ chief economics correspondent in Korea. The views expressed here are the writer’s own. — Ed.


khnews@heraldcorp.com