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Modeling AI-Driven Production and Competitiveness A Multi-Agent Economic Simulation of China and the United States

Yuxinyue Qian, Jun Liu

TL;DR

This work addresses how AI agents influence macroeconomic output and international competitiveness by China and the United States. It builds five progressively extended AI-enabled economic frameworks that couple human labor, AI collaboration, network effects, and autonomous AI production, analyzed via simulations with calibrated parameters and historical data. The results show a persistent US lead under collaboration but reveal strong catch-up potential for China when AI agents proliferate and capabilities mature, with synergy from simultaneous increases in agent scale and efficiency. The findings have policy relevance for balancing innovation incentives, industrial deployment, and R&D investment to shape the trajectory of the intelligent economy.

Abstract

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.

Modeling AI-Driven Production and Competitiveness A Multi-Agent Economic Simulation of China and the United States

TL;DR

This work addresses how AI agents influence macroeconomic output and international competitiveness by China and the United States. It builds five progressively extended AI-enabled economic frameworks that couple human labor, AI collaboration, network effects, and autonomous AI production, analyzed via simulations with calibrated parameters and historical data. The results show a persistent US lead under collaboration but reveal strong catch-up potential for China when AI agents proliferate and capabilities mature, with synergy from simultaneous increases in agent scale and efficiency. The findings have policy relevance for balancing innovation incentives, industrial deployment, and R&D investment to shape the trajectory of the intelligent economy.

Abstract

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.

Paper Structure

This paper contains 23 sections, 14 equations, 11 figures.

Table of Contents

  1. Introduction
  2. Related work
  3. Modeling Methodology
  4. Model 1: Pure Human Collaboration Model
  5. Model 2: Collaboration Model with AI Agents
  6. Model 3: AI Collaboration Model with Network Effects
  7. Model 4: AI as an Independent Productive Entity
  8. Model 5: Integrated Model with Independent AI Production and Network Effects
  9. Simulation Analysis
  10. Parameter Settings
  11. Baseline Scenario: Pure Human Collaboration between China and the United States
  12. Collaboration Model with AI Agents
  13. AI Collaboration Model with Network Effects
  14. AI as an Independent Productive Entity
  15. Comprehensive Model: AI as an Independent Productive Entity with Network Effects
  16. ...and 8 more sections

Figures (11)

  • Figure 1: Model 1: Comparison of outputs between China and the United States under pure human collaboration scenario
  • Figure 2: Model 2: Comparison of output multipliers between China and the United States under the AI collaboration scenario
  • Figure 3: Model 3: Comparison of marginal enhancement effects on total social output between China and the United States under network-effect AI collaboration
  • Figure 4: Comparison of total social output between China and the United States under Model 2 (AI collaboration) and Model 4 (AI independent production) with identical AI resource share ($\omega = 0.15$)
  • Figure 5: Model 5: Comparison of network-effect-induced output enhancement between China and the United States under the comprehensive model
  • ...and 6 more figures