In 2020, a “big” data center used 50 megawatts. By 2026, the new giants will each consume 1,000+ megawatts. That’s a 20x scale-up in just six years.
This isn’t incremental growth—it’s an architectural revolution.
Traditional data centers ran thousands of independent workloads. Today’s AI training clusters demand synchronized power across racks of GPUs working in concert on single model training runs. The infrastructure requirements are fundamentally different.
What does 1 gigawatt look like?
1 nuclear reactor’s output
750,000+ homes powered
100,000+ GPUs training simultaneously
$29 billion in investment
Big Tech hyperscalers—Amazon, Google, Meta, and Microsoft—have committed over $400 billion in capital expenditure, mainly on data centers. The spending has triggered fears of an AI bubble, but these companies argue demand still outstrips supply.
The constraint isn’t whether AI models can scale. It’s whether the power grid can keep up.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
