Eric Schmidt Warns: Artificial Intelligence May Drain the Earth's Power Supply
In a stark and urgent message, former Google CEO Eric Schmidt issued a warning that artificial intelligence (AI)—especially as it evolves toward artificial general intelligence (AGI)—could soon exceed the power capacity of global electricity grids, potentially triggering a large-scale energy crisis.
During a recent appearance on the Moonshots podcast and in congressional testimony, Schmidt emphasized that the true bottleneck in AI's growth is not chip design or software—but electricity. He stated, “Chips are advancing faster than our ability to power them. That’s the problem.”
1. Why Energy Is the Real Bottleneck—Not Chips
AI advancements have unlocked tremendous potential in healthcare, media, software development, and logistics. However, these breakthroughs come at a price: massive and growing energy consumption. Schmidt estimates that:
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The U.S. alone will need an additional 92 gigawatts of power by 2030 just to support AI infrastructure—equivalent to building 92 new nuclear power plants.
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Yet, in the past 30 years, only two nuclear plants have been constructed in the U.S., illustrating the scale of the challenge.
AI data centers are now consuming record levels of electricity and water, with Microsoft’s own reports showing a 34% increase in water use in just one year to cool AI servers.
2. The Silent Energy Arms Race
a. Tech Companies Are Competing for Power
Microsoft has signed long-term deals to restart old nuclear facilities like Three Mile Island to fuel AI data centers. Schmidt explained to Congress, “We need energy in all its forms—and we need it fast.”
He further noted:
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Current energy production rates can’t keep up with AI’s computing needs.
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Data centers for AI now require more power per square meter than most industrial factories.
By 2030, AI’s global demand may hit 96 gigawatts, rivaling the entire current energy usage of some developed nations.
b. AI vs. Climate Goals
As the climate crisis intensifies, this surge in energy use poses a contradiction:
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On one hand, AI could help optimize renewable energy usage and combat climate change.
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On the other, it threatens to derail climate progress by fueling more demand for fossil fuels.
Environmental groups like Greenpeace have expressed concern, warning that the AI boom might undermine decades of sustainability efforts unless urgent action is taken.
3. Environmental Dimensions: Electricity and Water
Beyond electricity, Schmidt warns of another limited resource: water.
AI server farms require massive amounts of clean water for cooling, especially in hot or dry regions. Some estimates suggest that:
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A single AI data center can consume as much water as a town of 10,000 people.
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This raises ethical and policy questions about water security, particularly in drought-prone areas.
In addition:
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Carbon emissions from AI infrastructure are increasing, especially when powered by non-renewable energy.
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E-waste from rapidly outdated AI hardware contributes to pollution and landfill overloads.
4. Global Implications of Schmidt’s Warning
a. U.S. Policy Response
In his testimony before the U.S. House Committee on Energy and Commerce, Schmidt urged lawmakers to:
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Fast-track approval processes for new energy projects.
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Establish national priorities for AI infrastructure support.
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Incentivize energy efficiency in tech development.
This aligns with the Biden administration’s broader strategy of modernizing the electric grid, expanding nuclear power, and scaling green hydrogen production.
b. International Reactions
Other nations are already reacting to the growing demand:
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Germany and the Netherlands are upgrading cooling systems for AI data centers.
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China is reportedly investing heavily in AI-dedicated hydroelectric and solar-powered plants.
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The EU is considering legislation to cap energy usage for high-risk AI systems.
These actions indicate a growing awareness that energy is now a geopolitical factor in the global AI race.
5. Schmidt’s Proposed Solutions
To prevent an AI-powered energy crisis, Schmidt offers a multi-layered plan:
1. Rapid Expansion of Energy Infrastructure
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Governments must prioritize solar, wind, geothermal, and nuclear projects.
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Red tape must be reduced to build energy capacity quickly.
2. Strategic Location of Data Centers
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AI servers should be built in regions with cooler climates and abundant water.
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Edge computing can help decentralize demand and reduce energy strain on urban grids.
3. Energy Efficiency in AI Models
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Developers must create more efficient algorithms that require fewer computations.
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Innovations like sparse modeling and quantization can reduce hardware demand.
4. Public-Private Cooperation
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Tech giants should partner with governments to share energy forecasts and align goals.
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Long-term investments in grid resilience and smart infrastructure are critical.
6. AI vs. Human Needs: What the Future Holds
By 2030, we may see:
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AI infrastructure competing with homes and hospitals for electricity.
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Governments regulating power usage by AI models during peak demand hours.
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New industries emerging to address clean energy demands for intelligent systems.
Schmidt emphasized, “This isn’t just a tech issue—it’s a human one. If we mismanage power, we mismanage everything else.”
His concern echoes wider fears in the AI community: that innovation without sustainability may bring more harm than good.
7. Final Thoughts: A Technological Crossroads
Eric Schmidt’s statements serve as both a technical alert and a moral wake-up call. As nations, companies, and individuals race toward an AI-driven future, the real question is no longer “Can we build it?” but rather, “Can we power it responsibly?”
In summary:
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AI is not only a data and chip issue—it’s a power problem.
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Future innovation depends on energy access as much as on engineering skill.
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Unless addressed urgently, the power demands of AI could become its greatest limitation.
By recognizing the stakes and acting decisively, humanity can ensure that AI becomes a sustainable force for good, rather than a short-circuited dream of progress.