Balancing Risk and Innovation: AI Governance Strategies in South Korea, Japan, and Taiwan
As AI becomes a defining force in global innovation and economic competitiveness, governments are establishing regulatory frameworks to oversee their use. Three of East Asia’s leading digital economies — South Korea, Japan, and Taiwan — are emerging as early movers in the development of AI laws, all aiming for more innovation-friendly regimes.
Diverse Approaches to AI Governance
Each jurisdiction has taken a distinct approach:
- South Korea: The AI Basic Act introduces an expansive risk-based regulatory regime.
- Japan: The AI Promotion Act favors a more permissive, innovation-driven model.
- Taiwan: The draft AI Basic Law proposes a principles-based framework that may develop into a more risk-based approach.
Together, these efforts offer a case study on the diversity of AI governance strategies and their effects on digital trade.
South Korea’s AI Basic Act
South Korea passed its Basic AI Act in January 2025. This Act, which introduces tiered obligations based on risk levels, applies to both AI developers and deployers. It is among the most ambitious regulatory efforts outside of the EU. Under Korea’s Act, providers of “high-risk” AI services must:
- Notify users in advance.
- Submit risk assessments and explainability documentation to government authorities before deployment.
The rushed development of the Act and lack of deep stakeholder engagement mean that many implementing details hinge on future regulations, which could establish additional obligations for AI systems that exceed certain computing power thresholds.
Japan’s AI Promotion Act
Japan followed with the passage of its AI Promotion Act in May 2025. This approach is incentive-driven, aiming to stimulate innovation through a light-touch regulatory framework. Rather than imposing sweeping new obligations, the Act defers to existing sector-specific regulations. It addresses concerns such as:
- Criminal misuse.
- Data privacy violations.
- Copyright infringement.
By promoting transparency measures, it stops short of mandating hard compliance requirements.
Taiwan’s Draft AI Basic Law
Taiwan is finalizing its own AI Basic Law. The draft legislation sets out principles centered on:
- Data governance.
- Transparency.
- Explainability.
- Fairness.
- Non-discrimination.
While imposing limited obligations, such as labeling or disclosure of AI-generated content, it addresses high-risk AI through standards, verification mechanisms, testing frameworks, and liability guidelines.
Comparative Insights and International Implications
With South Korea, Japan, and Taiwan charting distinct regulatory paths, they serve as a real-world testbed for how different approaches to AI governance affect innovation, investment, digital trade, and consumer welfare. All three jurisdictions reflect a mix of hard regulatory obligations and soft-law transparency- and incentive-based models.
Some early insights are emerging:
- Tiered risk models remain the most viable path forward, given the increasing ubiquitous application of AI across diverse sectors and use cases.
- Aligning with existing sectoral rules, where possible, helps reduce compliance burdens and fosters innovation.
- Proxy metrics such as compute thresholds may not reliably capture actual risk.
These approaches carry important international implications, as AI regulations increasingly intersect with cross-border service provision. Avoiding regulatory fragmentation is key to ensuring the continued flow of AI-enabled services and digital trade.
Conclusion
The varied approaches taken by South Korea, Japan, and Taiwan underscore the challenges of crafting AI governance frameworks that manage risks while avoiding disruption of digital trade. While all three emphasize risk management and international alignment, South Korea’s broad and accelerated approach highlights potential downsides of moving too quickly without fully developed implementing rules.
In contrast, Japan’s more measured, incentive-based strategy demonstrates advantages of building on existing legal frameworks to support innovation while addressing key risks. These early cases offer important lessons on the value of balanced regulatory approaches that uphold core principles for enabling trade in AI-enabled technologies.
