Taiwan has introduced a distinctive approach to AI governance that sidesteps the one-size-fits-all regulatory models adopted by the European Union and United States. On July 7, during the United Nations' "Global Dialogue on AI Governance" in Geneva, Taiwan's Ministry of Digital Affairs officially announced an "AI Risk Classification Framework" designed to guide how government agencies implement the country's AI Basic Act.

What Makes Taiwan's Framework Different From Other Major Economies?

Taiwan's AI Basic Act creates a regulatory structure that stands apart from approaches taken by the EU, the US, and other major Asian economies. The framework serves as the operational core of this system, translating high-level principles into concrete guidance that government agencies can actually use. Rather than imposing uniform rules across all sectors, Taiwan's model empowers sectoral regulators to assess risks specific to their industries and determine appropriate responses.

The framework provides general guidance alongside operational steps, workflows, and real-world examples that help regulators evaluate potential AI risks within their jurisdictions. This flexibility allows different sectors to tailor their approach based on their unique circumstances and risk profiles.

How Does Taiwan's Framework Guide Regulatory Action?

The framework gives sectoral regulators multiple tools to address identified risks. Depending on the severity and nature of the risk, regulators can take several approaches:

• Self-Discipline Guidelines: Encouraging industry to adopt voluntary standards and best practices without mandatory legal requirements.
• Pre-Deployment Screening: Requiring AI systems to be reviewed before they are put into use, ensuring they meet safety and performance standards.
• Licensing Requirements: Establishing formal approval processes for certain high-risk AI applications before deployment.
• Legislative Action: Proposing new laws or amendments to existing statutes that prohibit or restrict deployment of defined high-risk AI systems.

This graduated approach allows Taiwan to respond proportionally to different levels of risk rather than applying heavy-handed restrictions across the board. Government agencies are required to follow the framework's principles and methodology when implementing tasks under the AI Basic Act.

Who Is Bound by Taiwan's Framework, and Who Isn't?

An important distinction in Taiwan's approach is that the framework applies directly to the public sector. All government agencies must follow its principles and operational guidance. However, the private sector, including AI developers and companies deploying AI systems, is not directly bound by the framework itself.

That said, private companies will eventually face regulations and policies developed based on the framework's methodology. This means the framework serves as a blueprint not just for government implementation, but for future private-sector regulations as well. In essence, Taiwan is using its public-sector experience to inform how it will eventually regulate commercial AI deployment.

Why Does Taiwan's Approach Matter for Global AI Governance?

Taiwan's framework represents a middle path between the EU's prescriptive AI Act, which categorizes AI by risk level and imposes strict requirements on high-risk systems, and the US approach, which has historically favored lighter-touch regulation and industry self-governance. By creating a risk-classification system that gives regulators flexibility while maintaining clear principles, Taiwan offers a model that other countries might adapt to their own contexts.

The timing of Taiwan's announcement during the UN's Global Dialogue on AI Governance signals that the country is positioning itself as a thoughtful voice in international AI policy discussions. As governments worldwide grapple with how to balance innovation and safety, Taiwan's practical, sector-specific approach provides a concrete example of how risk-based governance can work in practice.