{
  "title": "Power Hungry: How AI Will Drive Energy Demand",
  "publication": "IMF Working Papers, April 22, 2025",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2025/04/21/power-hungry-how-ai-will-drive-energy-demand-566304",
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  "summary": "The development and deployment of large language models like ChatGPT across the world requires expanding data centers that consume vast amounts of electricity.",
  "sections": [
    {
      "heading": "Summary",
      "content": "- The development and deployment of large language models like ChatGPT require expanding data centers that consume vast amounts of electricity.\n- The paper uses descriptive statistics and a multi-country computable general equilibrium model (IMF-ENV) to examine how AI-driven data center growth affects electricity consumption, electricity prices, and carbon emissions.\n- Analysis of national accounts finds AI-producing sectors in the U.S. have grown nearly triple the rate of the private non-farm business sector.\n- Firm-level evidence shows electricity costs for vertically integrated AI companies nearly doubled between 2019-2023.\n- Simulations of AI scenarios in the IMF-ENV model are based on projected data center power consumption up to 2030.\n- The AI boom will cause manageable but varying increases in energy prices and emissions depending on policies and infrastructure constraints."
    },
    {
      "heading": "Key findings and statistics",
      "content": "- AI-producing sectors in the U.S. have grown nearly triple the rate of the private non-farm business sector.\n- Electricity costs for vertically integrated AI companies nearly doubled between 2019-2023.\n- Under scenarios with constrained growth in renewable energy capacity and limited expansion of transmission infrastructure:\n  - U.S. electricity prices could increase by 8.6%.\n  - U.S. carbon emissions would rise by 5.5% under current policies.\n  - Global carbon emissions would rise by 1.2% under current policies.\n- The analysis covers projected data center power consumption up to 2030."
    },
    {
      "heading": "Model, scenarios, and scope",
      "content": "- Model used: IMF-ENV, a multi-country computable general equilibrium (CGE) model.\n- Empirical evidence: national accounts analysis and firm-level electricity cost data.\n- Time horizon for projections: up to 2030.\n- Geographic focus: U.S. and global outcomes are examined; subject tags include Europe, North America, and Global."
    },
    {
      "heading": "Policy implications and recommendations",
      "content": "- Align energy policies with AI development to support AI expansion while mitigating environmental impacts.\n- Address infrastructure constraints by expanding renewable energy capacity and transmission infrastructure to limit increases in electricity prices and emissions.\n- Consider policy measures that can moderate the price and emissions impact from rapid data center and AI-related power demand growth.\n\nItalic: Source: Power Hungry: How AI Will Drive Energy Demand, IMF Working Paper No. 2025/081 (April 22, 2025).\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2025/04/21/power-hungry-how-ai-will-drive-energy-demand-566304"
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    "Authors: Christian Bogmans, Patricia Gomez-Gonzalez, Ganchimeg Ganpurev, Giovanni Melina, Andrea Pescatori, Sneha D Thube",
    "Published: April 22, 2025",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9798229007207.001",
    "The development and deployment of large language models like ChatGPT require expanding data centers that consume vast amounts of electricity.",
    "The paper uses descriptive statistics and a multi-country computable general equilibrium model (IMF-ENV) to examine how AI-driven data center growth affects electricity consumption, electricity prices, and carbon emissions.",
    "Analysis of national accounts finds AI-producing sectors in the U.S. have grown nearly triple the rate of the private non-farm business sector.",
    "Firm-level evidence shows electricity costs for vertically integrated AI companies nearly doubled between 2019-2023.",
    "Simulations of AI scenarios in the IMF-ENV model are based on projected data center power consumption up to 2030.",
    "The AI boom will cause manageable but varying increases in energy prices and emissions depending on policies and infrastructure constraints.",
    "AI-producing sectors in the U.S. have grown nearly triple the rate of the private non-farm business sector.",
    "Electricity costs for vertically integrated AI companies nearly doubled between 2019-2023.",
    "Under scenarios with constrained growth in renewable energy capacity and limited expansion of transmission infrastructure:",
    "The analysis covers projected data center power consumption up to 2030.",
    "Model used: IMF-ENV, a multi-country computable general equilibrium (CGE) model.",
    "Empirical evidence: national accounts analysis and firm-level electricity cost data.",
    "Time horizon for projections: up to 2030.",
    "Geographic focus: U.S. and global outcomes are examined; subject tags include Europe, North America, and Global.",
    "Align energy policies with AI development to support AI expansion while mitigating environmental impacts.",
    "Address infrastructure constraints by expanding renewable energy capacity and transmission infrastructure to limit increases in electricity prices and emissions.",
    "Consider policy measures that can moderate the price and emissions impact from rapid data center and AI-related power demand growth.",
    "**Working Paper**"
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