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This study introduces an LLMs-enabled policy computing method to quantitatively compare AI policy instruments across China, the US, and the EU based on a supply–environment–demand taxonomy. It identifies three distinct paradigms. China follows a supply-driven model focused on state-led capacity building. The US adopts a balanced strategy linking technological leadership with regulatory influence. The EU pursues a regulation-centric pathway prioritizing legal frameworks. Each paradigm is shaped by deeper political-economic structures shaping responses to generative AI. Global AI governance is following three diverging, coexisting trajectories. While their responses to generative AI were synchronized in timing, they diverged in direction and content, reinforcing rather than narrowing the distinctions among the three governance paradigms.
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Wu et al. (2026) studied this question.
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