When we look back on the period between 2023-2026, one of unprecedented capital expenditure driving the physical expansion of artificial intelligence, it will be with one of two takes: What were we doing? Or, why did we do that? Baseline models from Goldman Sachs suggest $765 billion will be the annual capital expenditure for chips, transmission lines and cooling equipment for AI. And that this will grow to $1.6 trillion annually by 2031. All for something as ethereal as an AI query. We talk about the infrastructure of AI, but we need to talk more about the data centers, power infrastructure to support the data centers, the water, and how we are having to renegotiate and rewrite what constitutes public use and property rights. We are making permanent physical decisions to satisfy the needs of a business model that we are still trying to collectively figure out. Utilities offer history lessons This is not the first time in our history that a technology has come along, and we have had to totally change our property laws to meet the moment. The railroads were an early technology that forced wholesale changes on us. Congress granted millions of acres of public land, and legislatures gave private corporations eminent domain power. Courts stretched the meaning of public use to enable commerce. This went on until the railroad companies got too big for their breaches and started gouging the farmers they had obtained the lands from with astronomical freight rates. Government had to step back in with the Interstate Commerce Act in 1887. The railroads became the first industry to be subject to federal regulation. The act required fair rates, no discrimination and rate transparency. This is where we started to see regulation of technologies considered utility. A subsequent rewriting of the rules came about for the electricity industry. Power companies, formerly monopoly franchises who got easements to U.S. farms had to accept the new rules that came with regulation after electricity was finally considered a utility. Power companies had to cap their returns on equity, become transparent about their rate setting and honor their legal obligation to serve everyone. Read more
Hyperscalers are utilities
Brief
Seyi Fabode argues hyperscalers and AI data centers are effectively becoming utilities, citing Goldman Sachs’ estimates of $765 billion/year in capex today for chips, transmission lines and cooling that could rise to $1.6 trillion/year by 2031. Fabode warns these permanent physical builds (power, water, land use) require revisiting property-law and public‑service rules, comparing the shift to railroads and the 1887 Interstate Commerce Act and later electricity regulation.
Why it matters
Goldman Sachs baseline models cited estimate $765 billion per year in capital expenditure for AI infrastructure — specifically chips, transmission lines, and cooling equipment — growing to $1.6 trillion annually by 2031.
Key details
- Author Seyi Fabode (Texas Energy & Power, published 2026-07-27) warns hyperscalers’ data centers and supporting power/water infrastructure are forcing redefinition of property rights and public use, drawing parallels to 19th‑century railroads (Congressional land grants, eminent domain) and the Interstate Commerce Act of 1887 and later electricity regulation (rate caps, transparency, universal service).