The subtitle of AI’s infrastructure story could be: “Beyond the Prompt: Where the Trillions Actually Go.” While the industry obsesses over model capabilities, the real constraints are emerging from power, water, and physical infrastructure.
The Infrastructure Economics framework identifies three converging challenges that will define AI’s trajectory:
1. The Power Crisis
The Stargate Project commits $500B, with each data center requiring 5 GW of power—more than New Hampshire’s entire electricity consumption. By 2030, AI data centers will consume 4.8% of global power generation. US data centers already consume 183 TWh annually—more than Malaysia’s entire national grid.
2. Water Stress
By 2030, AI could consume 450 million gallons of water daily—equivalent to 8 million people’s daily use. Half of US data centers are already located in water-stressed regions, creating direct competition between AI growth and local water needs.
3. Consumer Costs
Grid infrastructure costs are being socialized onto consumers. Virginia residents have seen electricity bills increase by $37.50/month. Average residential rates have climbed 4.8% since 2021. The public is subsidizing AI’s infrastructure buildout whether they use AI or not.
The strategic implication is profound: AI is an infrastructure story, not a softwarestory. Companies controlling power, chips, and data centers increasingly control AI’s future. Data center construction can’t keep pace with AI’s expanding compute demands.
Those betting on AI must also bet on infrastructure—or find themselves constrained by bottlenecks they can’t control.
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.
