TLDR: The energy consumption of AI chatbots and the data centers supporting them is expected to double by 2030, reaching approximately 945 terawatt-hours globally, a figure comparable to Japan’s current total electricity usage. This surge, driven by the rapid adoption of AI, raises significant environmental concerns and necessitates substantial investments in new power generation capacity.
A recent report, highlighted by SSBCrack News on September 14, 2025, indicates a significant environmental challenge on the horizon: the energy consumption of AI chatbots is projected to double by the year 2030. This alarming forecast is primarily attributed to the escalating demands of data centers, which are the backbone of rapidly advancing AI technologies. The International Energy Agency (IEA) has issued stark warnings and estimates, predicting that electricity use by data centers worldwide will more than double between now and 2030, reaching approximately 945 terawatt-hours (TWh) . This amount is slightly more than Japan’s current total electricity consumption, and it will account for nearly 3% of total global electricity consumption by that date .
In 2024, data centers already consumed about 1.5% of global electricity, totaling 415 TWh, but their growth is exponential . IEA Executive Director Fatih Birol emphasized the profound impact, stating, ‘AI is one of the biggest stories in the energy world today – but until now, policy makers and markets lacked the tools to fully understand the wide-ranging impacts’ . The rise of AI-related computation has transformed data centers into major power consumers, with AI-focused data centers alone expected to quadruple their electricity demand by 2030 .
The geographical distribution of this energy surge is concentrated, with the United States, Europe, and China currently accounting for about 85% of data center consumption . The United States is particularly poised to be the epicenter of this increase, with the IEA projecting that data centers will drive nearly half of the country’s electricity demand growth by 2030 . This will surpass the total power used for all energy-intensive industries combined in the US, and data centers could consume 8% of US power by 2030, up from 3% in 2022 . To meet this demand, US utilities will need to invest around $50 billion in new generation capacity solely for data centers . The IEA also warns that grid bottlenecks could delay 20% of planned data center projects, potentially impacting broader electrification goals .
The energy intensity of AI operations is evident in comparisons of query processing. A single ChatGPT query, for instance, requires approximately 2.9 watt-hours of electricity, which is nearly ten times more than the 0.3 watt-hours needed for a standard Google search . This significant difference underscores the substantial energy footprint of generative AI. While some AI innovations may boost computing speed faster than their electricity use, the widespread adoption of AI will inevitably lead to an overall increase in power consumption .
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- U.S. Grids Consider Emergency Disconnections for Energy-Intensive Data Centers Amid AI Boom
- Artificial Intelligence Poised for Transformative Growth, Approaching Human-Level Cognition by 2030, McKinsey Reports
Compounding the issue, efficiency gains in data center electricity use have dwindled since 2020, after a period where power demand remained relatively flat despite a near-tripling of workloads between 2015 and 2019 . This slowdown in efficiency, coupled with the accelerating AI revolution, is projected to cause data center power demand to grow by 160% by 2030 . Consequently, the carbon dioxide emissions from data centers may more than double between 2022 and 2030, raising serious concerns about the environmental impact of this technological advancement .
