The American South Has Quietly Become the Nation’s AI Superpower

It feels like AI infrastructure in the U.S. is spreading to every corner. However, recent research has highlighted that there are states representing clear pillars of AI chip production. While the American West and Silicon Valley may feel like the obvious choice for the region with the most rapid development, the South is the hidden champion, especially states like Texas and Tennessee. Surveys have revealed where the U.S.’s AI power and chip supply come from, and the most productive, plentiful clusters seem to be growing without limit. 

Exploring Industry Findings

AI data centers in the U.S. and chip production are continually expanding, with regions specializing in processing power or manufacturing. A study by Texas Royalty Brokers, a professional firm specializing in the sale of mineral and royalty rights, sought to assess the proliferation of these assets across all states and examine the relationship between the number of sites and the total number of units. 

Some clusters, like the 17 in Texas, are prioritizing graphics processing units (GPUs). Meanwhile, just four data centers in Tennessee house 1.27 million AI chips, making it the country’s uncontested leader. These are only portions of the 26 cluster sites in the American South. There are many other states with notable AI influence, as reflected in their data center density and chip output.

These are the top performers across 214 AI data centers in the U.S., represented as 83 cluster sites. The mystery is discovering how a state like Texas could have so many clusters yet fail to reach the chip accumulation of a state like Tennessee. Texas Royalty Brokers’ Eric Winegar suggested, “Tennessee is a great example of ‘few sites, massive scale.’ A large share of its chip total is driven by Memphis-area mega-buildouts — including xAI’s Colossus program — alongside major supercomputing infrastructure at Oak Ridge, so the state can show extremely high chip concentration even with fewer cluster locations.”

“Texas is more of a ‘many campuses’ market. There’s a broader spread of operators and projects, hyperscale builds and new AI infrastructure commitments, so Texas ends up with more distinct GPU cluster sites, even when chips are distributed across many locations.”

What Trends Could Experts Anticipate in 2026?

Based on these figures, industry professionals could make some assessments about what the coming year will look like for these facilities. AI infrastructure in the U.S. is an ongoing project, focused on scale and power. It is also about bolstering supply chain stability, as accessing raw materials for chips and an experienced labor force remains a mounting challenge.

Winegar noted, “These figures are a snapshot from the underlying GPU clusters and AI supercomputers dataset maintained by Epoch AI. The version we used for this report reflects their dataset as last updated December 30, 2025. Because many projects are announced, expanded or revised in phases, both chip totals and site counts can shift between dataset updates — especially for large ‘planned’ builds.”

These could keep the South as the main players, or insights from studies like these could motivate greater competition for projects that have yet to become public knowledge. By the end of 2026, states may have invested countless resources into raising their position in the AI sphere.

However, there are other data points experts can use to forecast data center expansion and potential power consumption, especially as the South gains an early foothold in the U.S. market. Analyses say these will be the primary drivers for chip and semiconductor advancements in the coming years:

• Customer preferences for personalized automation, data collection and smart tech
• Private and public investments in research and development, driving supply chains
• Motivation to improve macroeconomic performance by influencing GDP growth and employment
• Pressure to focus on innovation
• Need to discover technological optimizations for higher performance
• Urgency to reduce energy consumption for more sustainable technologies

The earlier states adopt strong AI clusters, the faster they will be able to capitalize on patient-focused health care solutions or inch closer to self-driving cars. Therefore, the short-term gratification of becoming known as an industry leader in chip housing and processing power leads to greater influence. However, the long-term gains are being able to apply these resources to positively impact all industries throughout the state.

Will Southern Grids Be Strong Enough to Sustain AI Data Centers in the U.S.?

Amid concerns about uncontrollable forces such as the climate crisis and cyclical weather patterns, some may wonder whether the South’s AI infrastructure can withstand the forces of nature. The buildings use varying amounts of power based on the area, with states like Texas consuming 15% of its 547 million megawatt-hours of annual electricity generation. California’s centers only use 1%, putting far less pressure on its grid. 

These figures could create hesitancy about faster expansion in the already empowered states, as their infrastructure may not withstand much longer without modernization and additional capacity. U.S. infrastructure is reaching the end of its life cycle, with energy scoring historically low on the Infrastructure Report Card. Much of it is beyond reasonable use, requiring large-scale overhauls before enabling more AI.

When considering influences like winter peak impacts on local grids, Winegar noted, “The energy portion of the report is state-level, so we don’t model winter peak constraints for a specific local utility or grid node. What we do include is an estimate of power draw and annual energy use at full load, which works well as an upper-bound indicator of potential grid exposure. For winter-specific risk, the biggest drivers are where the clusters interconnect — utility/ISO zone — whether demand lines up with regional winter peaks, especially during cold snaps, and what flexibility and backup generation is available.”

This implies several ways that states that are craving AI buildout need to also prioritize grid reinforcement and energy resilience. Infrastructure, like battery energy storage systems and microgrids, is one of several ways to democratize generation, reduce burdens on the primary grid and empower citizens toward decarbonization. These objectives are essential, especially as AI use, chip production, and processing power are increasing carbon emissions every year.

The Trajectory of AI Infrastructure in the U.S.

Stakeholders like Winegar are optimistic the South will maintain its hold as a national forerunner, saying, “The South has emerged as the preferred region for these facilities because of lower energy costs, available land and fewer regulatory barriers compared to other states. As more clusters come online, states will need to expand their power generation capacity significantly. What we’re seeing now is just the beginning of a much larger infrastructure buildout.”

These suggest the methods other states would need to follow suit. To become a national AI superpower, a multipronged approach and a strong grid are necessary to survive. Companies must consider how the South offers practical advantages, such as lower energy costs, as well as other potentially counterintuitive advantages, such as lower regulatory barriers. Determining what helps and hurts the sector will take years of collaboration and refinement until the U.S. has a fair playing field for all clusters.