Between 2025 and 2030, the International Monetary Fund (IMF) predicted that the economic benefits of artificial intelligence will increase global production by around 0.5% annually, outweighing the costs of increased carbon emissions from the data centers required to operate AI models.
However, an IMF study presented at its annual spring conference in Washington pointed out that such output benefits would not be distributed equally globally and urged companies and policymakers to minimize costs to society as a whole.
“Despite challenges related to higher electricity prices and greenhouse gas emissions, the gains to global GDP from AI are likely to outweigh the cost of the additional emissions,” it said.
“The social cost of these extra emissions is minor compared with the expected economic gains from AI, yet it still adds to the worrisome buildup of emissions,” it said in the report titled “Power Hungry: How AI Will Drive Energy Demand”.
Even while the world is struggling to meet its commitments to reduce carbon emissions, the adoption of AI is predicted to drive a boom in demand for energy-intensive data processing power in the years to come.
According to the IMF estimate, the area devoted to server-filled warehouses in northern Virginia—home to the greatest concentration of data centers in the world—is already around the size of eight Empire State Buildings.
AI-driven global power demand is predicted to more than quadruple to 1,500 terawatt-hours (TWh) by 2030, which is about equal to India’s current electricity usage and 1.5 times greater than the demand for electric cars during the same time frame.
The ability of IT companies to fulfill their pledges to reduce data center emissions through greater use of renewable energy sources and other strategies will determine the carbon footprint of that growth.
COULD AI LEAD TO ENERGY EFFICIENCY GAINS?
According to IMF estimates, a significant adoption of AI would result in a 1.2% worldwide cumulative rise in greenhouse gas emissions between 2025 and 2030 under present energy policy. According to their calculation, greener energy measures would keep that growth to 1.3 Gt.
The societal cost of those emissions, calculated at $39 per ton, was estimated to be between $50.7 and $66.3 billion, less than the economic benefits from the 0.5% yearly increase in global GDP that AI was supposed to provide.
The way AI is applied, particularly if it can result in energy efficiency gains or more sustainable patterns of consumption overall, will determine its economic and environmental effects, according to independent analysts.
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