U.S. AI startup Anthropic’s recent rollout of its next-generation large language models—which faced brief government-mandated restrictions on foreign access before global services resumed—has drawn intense international scrutiny. He-Tien Huang, an analyst at the Center for International Trade Policy of the Chung-Hua Institution for Economic Research (CIER), highlighted that this incident highlights a shift in U.S. governance concerning frontier AI technologies that expands oversight from merely focusing on chip supply to also encompassing the model level. It also illustrates the dynamic nature of AI governance as it balances innovation, manages risks, and opens markets, highlighting the potential for rapid policy shifts. For Taiwan, the priority should not be chasing the race for general-purpose frontier models, but rather deepening its pivotal role in the global AI supply chain and cementing its status as a trusted U.S. partner.
AI Governance Expands from Chips to Models; National Security Drives Policy Intervention
Analyst Huang noted that after Anthropic released its Mythos5 and Fable5 large language models in June, the U.S. Department of Commerce temporarily suspended foreign user access due to national security concerns. However, about three weeks later, the department lifted the restrictions and restored global access. This marks the first time the U.S. has shifted its AI governance focus from hardware export controls to large language models. It underscores that current AI policy is no longer confined to chips and computing equipment, but is progressively encompassing algorithms and the models themselves.
In recent years, overarching U.S. AI policy has remained centered on encouraging innovation. This includes advancing full-stack AI development, promoting corporate self-regulation, and establishing security governance mechanisms for frontier models via executive action. However, the Anthropic incident demonstrates that when national security or major risk assessments are involved, the U.S. government can swiftly impose restrictions. This reflects that AI governance now weighs both technological advancement and economic security.
AI Governance Moves Toward Institutionalization; Trusted Partners Face Tiered Management
The Anthropic incident also indicates that future international AI cooperation will place greater emphasis on security and trust mechanisms. Analyst Huang noted that as the capabilities of frontier models continue to advance, the U.S. will likely establish a more comprehensive, tiered governance system, treating these models as strategically significant assets rather than standard commercial products.
The U.S. has consistently promoted the concept of “Trusted Partners” in recent years by applying differentiated management based on varying risk levels in advanced chips, cloud computing, and AI technology cooperation. Even like-minded allies may be subject to different cooperation models depending on their technological tier. Economies such as the European Union and Canada have also actively pursued autonomous AI capabilities recently, seeking to reduce reliance on any single technology source. This signals that global AI governance is evolving toward a balance of cooperation and autonomous development.
Leveraging Supply Chain Advantages to Cement Taiwan’s Competitive Edge
For Taiwan, its greatest current advantage remains its highly irreplaceable hardware supply chain—encompassing semiconductor manufacturing, advanced packaging, and AI servers. This serves as a vital foundation for its participation in global AI development.
Analyst Huang argued that rather than pouring resources into the race for general-purpose frontier models, Taiwan should focus on its inherent strengths. While continuously deepening the competitiveness of its hardware supply chain, Taiwan should accelerate the development of application-specific AI models for sectors such as smart manufacturing, healthcare, linguistics and culture, national defense, and critical infrastructure. This approach will build autonomous technological capabilities and industrial resilience. Such models address local needs and practical applications, helping to maximize the tangible benefits of AI while mitigating the risk of relying on foreign critical technologies.
Strengthening U.S.-Taiwan Cooperation; Balancing Autonomy and Industrial Resilience
The Anthropic incident reveals that future international AI governance will increasingly prioritize security, trust, and tiered cooperation mechanisms. Taiwan must continue to consolidate its core position in the semiconductor and AI hardware supply chains and strengthen cooperation with the U.S. and like-minded partners. Concurrently, it should persistently cultivate AI talent, strengthen basic research, and develop application-specific AI technologies to establish autonomous deployment capabilities.
Looking ahead, AI will progressively become a critical general-purpose technology and infrastructure. The focus of global competition will pivot from a sheer arms race in model capabilities toward institutions, regulations, and supply chain positioning. If Taiwan can continue to capitalize on its hardware advantages, strengthen international cooperation, and improve its AI application capabilities, it will not only secure its vital role in the global AI supply chain but also maintain its competitive edge in the next wave of AI governance frameworks. This will lay a strong foundation for long-term industrial development and economic security.
Author: CIER Editorial Team
Date: July 20, 2026