"I Wish I Could've Predicted It": The $27 Billion Gas Deal Behind AI's Energy Appetite

The recent $27 billion gas deal between NextEra Energy Resources and a group of investors has sparked conversation about the role of natural gas in the energy transition. While the deal was initially seen as a boon for the gas industry, it has since been revealed that the primary driver behind the increased demand for natural gas is the energy-intensive nature of artificial intelligence (AI) operations. This article explores the connection between AI and natural gas, and the implications for the energy sector and the environment.



The rapid growth of AI, particularly generative models like Stable Diffusion XL and GPT-4, has contributed to the increased demand for natural gas, as evidenced by the $27 billion gas deal. This is due to the energy-intensive nature of training and operating these models, which requires significant computational power and thus electricity. As the demand for AI services grows, so does the need for energy to power the data centers and servers that support these models. This increased demand for electricity has led to a surge in natural gas consumption, as it is often used to generate electricity.



According to the International Energy Agency (IEA), electricity consumption from data centers, AI, and cryptocurrency could reach double 2022 levels by 2026, accounting for at least one Sweden or at most one Germany's electricity demand. However, it's important to note that these numbers are not just for AI, as it's difficult to nail down AI's specific contribution to electricity demand from data centers. In comparison, other sectors' energy demands are much higher. For instance, the IEA projects that the world will add about 3,500 TWh of electricity demand over the same period, with electric vehicles and the industrial sector being bigger sources of growth in electricity demand than data centers in the European Union.

While AI's energy consumption is a concern, it is not the primary driver of global electricity demand growth. Other sectors, such as electric vehicles and the industrial sector, have a more significant impact on overall energy consumption. However, the localized nature of AI's energy demand can lead to challenges in specific regions, requiring targeted solutions to address these issues.

To balance their climate goals with the rising energy demands of AI, tech companies like Microsoft and Google can adopt a multi-faceted approach that combines renewable energy adoption, energy efficiency, and carbon offsetting strategies. By investing in renewable energy sources, improving energy efficiency, and utilizing carbon offsetting programs, these companies can help mitigate the environmental impact of their AI operations while still achieving their sustainability goals.

In conclusion, the $27 billion gas deal highlights the connection between AI and natural gas, and the need for tech companies to address the energy demands of their AI operations. By adopting a balanced approach that combines renewable energy adoption, energy efficiency, and carbon offsetting, these companies can help ensure a more sustainable future for both the energy sector and the environment.