South Korea's AI National Strategy, anchored by the Basic Act on Artificial Intelligence that took effect in 2025, represents one of the most ambitious attempts by a mid-size economy to establish itself as a global AI leader. The strategy targets KRW 455 trillion (approximately $340 billion) in economic surplus by 2030, massive GPU infrastructure buildout, sovereign open-source AI models, and nationwide AI literacy. Whether these ambitions are achievable depends on the country's ability to overcome structural challenges that the strategy acknowledges but may not adequately address.
The Legal Framework
Lee (2025), in the Asian Journal of Law and Society, provides an overview of Korea's AI framework, examining its main features and challenges. The Basic Act on AI establishes a rights-based approach that draws on both EU and US precedents while incorporating distinctively Korean elements. It creates an AI Committee under the Prime Minister's office, mandates impact assessments for high-risk AI, and establishes a national AI ethics framework.
The framework's distinctive feature is its emphasis on AI industry promotion alongside rights protection — a dual mandate that other jurisdictions have typically separated. The EU AI Act focuses primarily on risk management; the US approach focuses primarily on innovation promotion. Korea attempts both simultaneously, creating potential tensions when promotional and protective objectives conflict.
Legal Challenges
Kim (2025), in the Korean Journal of Communication Law, examines the legal challenges following the Basic Act's enactment. Key issues include the definition of AI systems (broad enough to capture relevant technologies but narrow enough to avoid regulating ordinary software), the scope of impact assessments (which AI applications require formal assessment and which do not), and the enforcement mechanisms (how the AI Committee will exercise oversight authority in practice).
The definition challenge is particularly acute. Korea's technology landscape includes globally competitive semiconductor firms, major platform companies, active startup ecosystem, and a sophisticated consumer market. The regulatory framework must accommodate this diversity without creating compliance burdens that disadvantage Korean companies relative to foreign competitors or stifle the innovation the strategy is designed to promote.
The Infrastructure Race
Shim and Suh (2025) conduct a comparative study of national high-performance computing strategies between South Korea and the United States. The comparison reveals the scale of the infrastructure challenge Korea faces. The US has decades of accumulated HPC investment and deep talent pools. Korea is building rapidly but from a smaller base, and the global competition for GPU supply — driven by AI training demand from every major economy simultaneously — means that infrastructure buildout depends on supply chain access that cannot be taken for granted.
Korea's strategy includes development of sovereign AI foundation models — large language models trained on Korean data that can serve Korean-language applications without dependency on foreign providers. This initiative addresses a genuine gap: global AI models perform significantly worse on Korean than on English, and reliance on foreign models for Korean-language AI applications creates both quality and sovereignty concerns.
The broader lesson from Korea's strategy is that AI national policy requires simultaneous action across multiple domains — legal framework, infrastructure investment, talent development, industry promotion, and international engagement — and that weakness in any single domain can constrain progress across all others. The ambition is clear; the execution challenge is whether a mid-size economy can sustain coordinated action across all these fronts simultaneously.
The Talent and Ecosystem Challenge
Korea's most significant challenge may be talent. The country produces strong engineering graduates, but many of Korea's most talented AI researchers work at American companies and universities. The brain drain toward Silicon Valley — driven by higher salaries, larger datasets, and more powerful compute infrastructure — undermines the domestic capability that the national strategy depends on.
The strategy addresses this through investment in AI graduate programs, research centers, and industry-academia partnerships. But the competition for AI talent is global and intensifying. Every major economy is simultaneously trying to attract and retain AI researchers, creating a seller's market where compensation packages and research resources matter more than national loyalty.
Korea's ecosystem advantages include a highly connected population (the world's highest smartphone penetration), advanced digital infrastructure (nationwide 5G coverage), sophisticated consumer expectations, and a culture of rapid technology adoption. These create favorable conditions for AI application development and deployment. The question is whether the application ecosystem can sustain a globally competitive AI research base, or whether Korea will remain primarily an adopter rather than originator of frontier AI capabilities.
The relationship between Samsung, SK, and the national AI strategy adds another dimension. Korea's conglomerates (chaebol) have the scale to invest in AI research and infrastructure, but their priorities are driven by global competitive positioning rather than national strategy alignment. Coordinating chaebol AI investment with national policy goals requires governance mechanisms that balance industrial autonomy with strategic direction.