Why the AI Revolution Will Require Massive Energy Resources

Rachel Lomasky

Chief Data Scientist

April 24, 2025

About this blog

AI Is Driving Data Center Energy Spikes: Generative AI workloads are rapidly increasing electricity consumption in data centers, which could reach up to 12% of total U.S. demand by 2028.

Training and Inference Are Power-Hungry: Training large models consumes massive energy, and while inference is lighter, its scale across millions of queries adds significant load.

Specialized Hardware Adds to the Strain: GPUs and TPUs are efficient for AI tasks but draw high power and require energy-intensive cooling systems.

Efficiency Gains Haven’t Caught Up: Improvements in chip design and cooling help, but they haven’t offset the exponential rise in AI-related power demand.

AI Can Also Save Energy Elsewhere: Despite its footprint, generative AI can increase efficiency in sectors like transportation, agriculture, and manufacturing, potentially offsetting some of its energy use.

This week, Lynne Kiesling (Director of the Institute for Regulatory Law & Economics at Northwestern Pritzker's Center on Law, Business, and Economics; Research Professor at the University of Colorado, Denver) and I discuss the ways in which the rapid rise of generative AI has triggered a sharp escalation in data center electricity consumption, with profound implications for national energy use, system planning, and climate goals.

The article is in Civitas Outlook, the online journal of the Civitas Institute at UT Austin, which publishes original writing about the ideas that create flourishing societies. You can read it at: https://www.civitasinstitute.org/research/why-the-ai-revolution-will-require-massive-energy-resources

Rachel Lomasky

Chief Data Scientist

About

Rachel

Rachel Lomasky is the Chief Data Scientist at Flux, where she continuously identifies and operationalizes AI so Flux users can understand their codebases. In addition to a PhD in Computer Science, Rachel applies her 15+ years of professional experience to augment generative AI with classic machine learning. She regularly organizes and speaks at AI conferences internationally - keep up with her at her LinkedIn here.

About Flux

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