Modeling AI-Driven Production and Competitiveness A Multi-Agent Economic Simulation of China and the United States
It provides a model-based framework for understanding AI-driven production transformation and international competitiveness shifts, with quantitative insights for policy, but is incremental as it builds on an existing multi-agent economic model.
This paper simulated macroeconomic output evolution in China and the US under AI-driven production mechanisms, finding that AI as an independent productive entity leads to far higher social output growth rates than traditional human-labor models, and China shows potential for acceleration in intelligent agent populations and technological catch-up.
With the rapid development of artificial intelligence (AI) technology, socio-economic systems are entering a new stage of "human-AI co-creation." Building upon a previously established multi-level intelligent agent economic model, this paper conducts simulation-based comparisons of macroeconomic output evolution in China and the United States under different mechanisms-AI collaboration, network effects, and AI autonomous production. The results show that: (1) when AI functions as an independent productive entity, the overall growth rate of social output far exceeds that of traditional human-labor-based models; (2) China demonstrates clear potential for acceleration in both the expansion of intelligent agent populations and the pace of technological catch-up, offering the possibility of achieving technological convergence or even partial surpassing. This study provides a systematic, model-based analytical framework for understanding AI-driven production system transformation and shifts in international competitiveness, as well as quantitative insights for relevant policy formulation.