AI’s Carbon Footprint Exposed

February 27, 2025

5 minutes read

Data center with cooling towers, highlighting AI's energy and water use. — This image underscores the physical infrastructure powering AI, drawing attention to the significant energy and water demands of data centers

Key Points

Research suggests AI training consumed energy equivalent to powering a small country in 2024, sparking climate concerns.
It seems likely that environmentalists are pushing for sustainable AI regulations due to high energy use.
The evidence leans toward tech leaders arguing AI’s benefits, like climate modeling, outweigh emissions.

Introduction

In 2025, as record heatwaves highlight the climate crisis, a new investigation has revealed the significant energy demands of training large AI models. This has ignited a debate between environmentalists and tech industry leaders, with each side presenting compelling arguments. Below, we explore the energy consumption of AI, the concerns raised, and the industry’s response, aiming to provide a clear picture for those new to the topic.

AI’s Energy Consumption

Training massive AI models, such as those behind chatbots like ChatGPT, requires vast amounts of energy. Estimates indicate that in 2024, the total energy used for training these models reached around 1 terawatt-hour (TWh), comparable to the annual energy use of a small country. This figure underscores the scale of AI’s environmental footprint, particularly as the demand for such models continues to grow.

Environmental and Industry Perspectives

Environmentalists are alarmed by AI’s energy consumption, arguing it contributes to greenhouse gas emissions and exacerbates climate change. They are advocating for regulations to ensure AI development is sustainable, highlighting the need for transparency in energy use. Conversely, tech leaders contend that AI’s benefits, such as enhancing climate modeling and optimizing renewable energy systems, justify its environmental impact. This clash has created a contentious dialogue, with both sides seeking to balance innovation and sustainability.

Unexpected Detail: Water Usage

Beyond energy, AI’s reliance on data centers also strains water resources for cooling, with some centers consuming billions of gallons annually, adding another layer to the environmental debate.

Survey Note: Detailed Analysis of AI’s Environmental Impact and Industry Debate

In the context of 2025’s record heatwaves, an investigation has exposed the significant carbon footprint of AI, particularly in training large models, with energy consumption estimated at levels sufficient to power a small country in 2024. This has triggered a robust debate between environmentalists and tech industry leaders, each presenting distinct perspectives on AI’s role in the climate crisis. Below, we delve into the specifics, drawing from extensive research to provide a comprehensive overview.

Energy Consumption of AI Training

Training massive AI models, such as those behind chatbots like ChatGPT, requires vast amounts of energy. Estimates indicate that in 2024, the total energy used for training these models reached around 1 terawatt-hour (TWh), comparable to the annual energy use of a small country. This figure underscores the scale of AI's environmental footprint, particularly as the demand for such models continues to grow.

The energy required to train large AI models is substantial, driven by the computational power needed for processing vast datasets. For instance, training GPT-3, a large language model, consumed approximately 1,300 megawatt-hours (MWh), equivalent to powering 130 US homes annually. More advanced models, like GPT-4, reportedly required over 50 gigawatt-hours (GWh), or 50,000 MWh, for training, highlighting the escalating energy demands as models grow in complexity.

To estimate the total energy consumption for training massive AI models in 2024, research suggests that if around 20 such large models were trained, each consuming about 50 GWh, the total could reach approximately 1 TWh. This figure aligns with the annual energy consumption of small countries, such as those consuming less than 1 billion kilowatt-hours (1 TWh) per year, as noted in energy consumption statistics Energy Consumption by Country 2024.

Environmentalists’ Concerns and Calls for Regulation

Climate activists and environmental groups have expressed significant concern over AI’s energy consumption, viewing it as a contributor to greenhouse gas emissions. Reports indicate that data centers, crucial for AI operations, could account for up to 9% of US electricity by 2030, driven by AI demands Data centers could use 9% of US electricity by 2030, research institute says | Reuters. This has led to protests, particularly in regions like Latin America, where data center expansion is seen as risking water and energy crises Critics fear catastrophic energy crisis as AI is outsourced to Latin America.

Climate activists protesting outside a tech company over AI's environmental impact.

Environmentalists are pushing for “sustainable AI” regulations, emphasizing the need for transparency in energy use and carbon emissions. A coalition of groups has warned that AI could increase energy use and accelerate climate misinformation, challenging claims that it will solve the climate crisis AI likely to increase energy use and accelerate climate misinformation – report | The Guardian. They argue for a halt to unchecked data center growth and comprehensive assessments of AI’s life-cycle impacts.

Tech Industry’s Defense and Benefits

Tech industry leaders, however, argue that AI’s benefits outweigh its emissions toll. They highlight applications like climate modeling, which can predict weather patterns and optimize renewable energy systems, potentially mitigating climate change impacts. For example, AI is used to track illegal fishing, predict wildfires, and enhance energy grid efficiency, suggesting a net positive environmental impact AI and energy: Will AI reduce emissions or increase demand? | World Economic Forum.

Companies like Microsoft and Google, despite reporting increased emissions (up 30% and 48% respectively since 2020 and 2019), are investing in renewable energy and energy-efficient data center designs. Microsoft, for instance, has pledged to achieve carbon negativity by 2030, though recent reports show emissions rising due to AI-related data center expansion AI is an energy hog. This is what it means for climate change. | MIT Technology Review. Industry leaders like Bill Gates have urged against overreacting to AI’s energy demands, emphasizing potential innovations Fighting the Power Deficiency: The AI Energy Crisis – AlgorithmWatch.

The Debate and Conflict

This conflict manifests as a “showdown” between green groups advocating for regulations and tech leaders defending AI’s utility. Environmentalists criticize the industry for prioritizing market dominance over climate goals, with some suggesting that AI’s energy demands could delay fossil fuel plant retirements Will AI Revolutionize Clean Energy or Destroy a Functioning Climate Ecosystem? – Newsweek. Conversely, tech firms argue that AI’s ability to accelerate clean energy solutions justifies its current environmental footprint, creating a contentious dialogue.

Additional Environmental Impacts: Water Usage

An unexpected detail is AI’s water consumption for cooling data centers, with Google using 5 billion gallons in 2022, a 20% increase from 2021, and Microsoft seeing a 34% rise As Use of A.I. Soars, So Does the Energy and Water It Requires – Yale E360. This has led to protests in regions like Chile and Uruguay over data centers tapping drinking water reservoirs, adding another dimension to the environmental debate.

Efforts Toward Sustainability

Both sides are exploring solutions. Environmentalists support initiatives like capping power usage during AI training, potentially reducing consumption by 12-15% How to manage AI’s energy demand — today and in the future | World Economic Forum. Tech companies are investing in renewable energy and liquid cooling systems to improve efficiency, though challenges remain in scaling green energy to meet AI’s demands.

Conclusion and Future Outlook

The debate over AI’s environmental impact is far from resolved, with 2025 highlighting the urgency of balancing innovation and sustainability. As AI continues to evolve, collaborative efforts between tech firms, policymakers, and environmentalists will be crucial to ensure that its development aligns with global climate goals, potentially transforming AI into a tool for a greener future.