Full Title: Future-Proof AI Data Centers, Grid Reliability, and Affordable Energy: Recommendations for States
Author(s): Nora Wang Esram and Camron Assadi
Publisher(s): American Council for an Energy-Efficient Economy
Publication Date: April 7, 2025
Full Text: Download Resource
Description (excerpt):
Artificial intelligence (AI) is transforming industries, but its rapid expansion is already causing a significant increase in electricity demand. Data centers that support AI model training and inference require immense computational power, putting pressure on the electric grid and raising concerns about sustainability, energy costs, and reliability. Recent projections suggest that AI-driven data centers could consume up to 9% of U.S. electricity by 2030 (equivalent to the electricity needed to power 20–40% of today’s vehicles if they were EVs), highlighting the need for policies that ensure energy-efficient, socially responsible, and environmentally sustainable development.
The emergence of DeepSeek, a highly efficient AI model, highlights a new path forward: prioritizing software and system-level optimizations to reduce energy consumption. Unlike traditional AI models that rely on massive hardware scaling, DeepSeek achieves competitive performance with a fraction of the energy use. This underscores the need for AI infrastructure planning focused on efficiency.
This white paper is intended for state legislators and regulators who want to establish prudent policies to guide the growing AI data center industry. If AI data centers are overbuilt and become stranded assets, they threaten to raise other electricity customer energy costs and strain the electric grid. Energy-efficient data centers can avoid these outcomes, but only with specialized efficiency metrics based on up-to-date data from the GenAI industry.