(pictures show before and after of a couple Data Centers that were built in Virginia and Georgia after they scalped the forests and suffocated the earth with concrete)

“If we peel back the metaphor, what we find is staggering.

The United States alone now houses data centers that consume roughly as much electricity as many entire nations. And they are expanding at a pace that even utilities admit they can’t keep up with. One analysis suggests that nearly half of the world’s data-center electricity consumption occurs in the U.S. The new AI-optimized facilities are larger, hotter, thirstier, and far more power-hungry than their predecessors.

And outside the U.S.?

The explosion is even more dramatic.

Across Mexico, Brazil, Malaysia, Indonesia, Kenya, South Africa, and Ireland, hyperscale data centers are rising like industrial cathedrals. These are not the modest server rooms of the early internet era. These are multi-million-square-foot complexes built with the assumption that the future will demand more computation, more inference, more generation, more energy. Always more.

A brief accounting of the water, energy, and materials flowing into the AI revolution.

Water :

-By 2027, AI data centers could consume 6.4 trillion liters of freshwater annually. That’s enough to fill 2.8 million Olympic swimming pools.

-Microsoft already draws 42% of its water from regions officially classified as “water-stressed.”

-Google reports 15% of its data-center water use occurs in “high water scarcity” areas, and that number is rising.

-A single hyperscale AI complex can require millions of gallons per day just for cooling.

-Water withdrawals for AI compete directly with human drinking water, agriculture, and the ecological flows that keep rivers alive.

Energy :

-Global data-center power consumption is projected to reach ~1,000 TWh/year by 2030, or roughly equivalent to the electricity use of Japan.

-AI will likely account for 40–60% of this surge, making it one of the fastest-growing energy loads on the planet.

-U.S. data centers alone already consume as much electricity as entire nations, and expansion pressures utilities to revive fossil fuel generation.

-Coal plants in the U.S. and Europe are being kept alive, or reactivated, specifically to feed AI server clusters.

-Nuclear power is being revived at an unprecedented scale to meet AI’s 24/7 baseload demand, triggering a new wave of uranium mining on Indigenous land.

-AI is not “efficient.” It is becoming one of the most energy-intensive technologies humanity has ever built.

Materials and Mining :

-To meet AI’s copper needs alone, the world may need to mine as much copper in the next 25 years as in all of human history to date.

-AI chips require 10–15× more energy and water to manufacture than standard chips.

-Server lifespans are shrinking to 3–5 years, accelerating the world’s fastest-growing toxic waste stream: e-waste.

-Each AI accelerator chip contains layers of rare metals that are currently impossible to recycle economically.

-New mining and processing demands fall overwhelmingly on the Global South: the Atacama Desert (lithium), the Congo (cobalt), Indonesia (nickel), the Navajo Nation and Kazakhstan (uranium), Chile and Peru (copper).

The “intelligence” of AI rests on an explosion of extraction, massive new wounds on land, watersheds, and communities.”

- Justin McAffee (from his post titled “What We Burn to Speak to Machines : Inside the Global AI Buildout: Power, Water, and Sacrifice Zones”)