2025年全球人工智能影响报告_33页_2mb

The Global Impact of AI: Mind the Gap

• AI Impact and Inequality: Advanced Economies (AE) benefit the most from AI-driven productivity gains, potentially achieving more than double the income gains compared to Low-Income Countries (LICs).

• Key Determinants: AI’s global impact is shaped by three main factors: sectoral exposure to AI, preparedness to integrate it into the economy ( Institutional framework, digital infrastructure, skilled workforce), and access to necessary technologies and data.

• Model Findings:

  • GDP Growth: Under a high-TFP growth scenario, global GDP could rise by nearly 4% in ten years, while LICs would see minimal gains.
  • Sectoral Effects: AI-intensive sectors (e.g., Pharmaceuticals, Computers) exhibit the highest productivity gains, followed by non-tradable services (e.g., Education, Healthcare).
  • Exchange Rates: AI-driven productivity increases in non-tradable sectors could lead to real depreciation of AE currencies relative to EMs and LICs, due to an "Inverse Balassa-Samuelson Effect".

• Policy Considerations:

  • Limited Access Scenario: AI adoption restrictions in EMs and LICs would exacerbate economic disparities.
  • Enhanced Preparedness: Improving institutional readiness and digital infrastructure in EMs and LICs can mitigate, though not fully eliminate, the gap.
  • Access Improvements: Increasing availability of AI technologies, data, and computational resources can help balance global benefits.

• Suggestions for Further Research:

  • Refine labor market modeling to capture nuanced impacts of AI-driven structural change.
  • Analyze within-country distributional consequences, such as effects on wage inequality and wealth concentration.

Key Conclusions:

• Global GDP Impact: AI-induced productivity gains could boost global GDP by up to 4% in ten years under a high-TFP scenario.
• Country-Specific Outcomes: AEs, particularly the US, are likely to experience the largest output increases, while LICs face the least gains.

Recommendations:

• Prioritize investments in digital infrastructure, human capital, and regulatory frameworks for EMs and LICs.
• Encourage international collaboration to enhance access to AI technologies and data.
• Address distributional effects, such as wage inequality and wealth concentration, to ensure inclusive benefits from AI adoption.