The Hidden Cost of AI: Federal AI Investment and Rising Energy Prices

This study examines the economic impacts of artificial intelligence (AI) investment, with a particular focus on energy costs. We combine quarterly cost-of-living data from the Council for Community and Economic Research (C2ER) with federal grant information from USAspending.gov to explore how AI-related public investment affects regional energy prices across the United States. The C2ER data are drawn from the Cost-of-Living Index (COLI) project, a nationwide initiative that tracks prices of multiple goods and services, including monthly energy costs in a standardized house, across metropolitan areas.

Our analysis focuses on regions that have consistently received federal grants aimed at supporting AI development. We construct measures of total AI-related fundings received over time and examine their relationship with local energy prices. The results reveal a strong positive association between long-run accumulated AI grants and energy costs–to be specific, costs of electricity and natural gas. Additionally, based on the correlations between C2ER data and data-center power usage, we find preliminary evidence that areas where data centers consume more power tend to face higher electricity prices.

We therefore interpret these findings as follows. The rapid expansion of AI-related infrastructure–especially energy-intensive data centers–places substantial pressure on local energy systems. This increased demand may strain existing infrastructure and raise energy prices, which are ultimately passed on to the households. By highlighting an important but often overlooked channel through which AI investment affects local economies, this study contributes to the broader discussion on the unintended distributional and inflationary effects of public investment in AI.