Big Tech Will Go Global in Its Quest for Cheap Energy

In the southern tip of Malaysia is the state of Johor, famous for its beaches and mountainous forest. But Johor has a new boom industry: AI-powered data centers, and Microsoft is making more than $2 billion in such data centers. For tech giants, electricity has become the new oil. A modern AI data center may require 90 MW, enough to power tens of thousands of American homes. With the growth of AI applications, from chatbots to AI agents, the needs are growing. The industry consortium plans data centers that require 10 GW (more than 100 times the demand of today’s CEO). Finding cheap, reliable power is now essential for technology companies like silicon chips.

By 2025, major technology firms will be looking around the world for kilowatts, megawatts and gigawatts. In board meetings, discussions about server capacity are increasingly overshadowing discussions about grid capacity and the future of energy. Nations blessed with an abundance of cheap energy are using this new advantage and policies to attract AI investors with the enthusiasm once reserved for manufacturing.

Regions that have historically won the data center boat, such as Ireland and Singapore, have found their hard power to explode ahead of the GenAI boom. This created opportunities for potential competitors, not only Malaysia but Indonesia, Thailand, Vietnam, and Chile. The delay is less important than keeping the electrons flowing.

Cheap energy has long been a priority for firms: Just as companies in the past clustered their refineries near ports, their factories near coal mines, AI firms are trying to locate themselves near where they can get consistent electricity—and it’s great. values.

Location is ultimately important. Half of the energy costs in a data center typically come from using cooling and air conditioning systems to keep servers from overheating. Cooler climates or coastal areas will become more desirable as potential locations.

This push to bring AI is so powerful that big tech firms are buying dirty energy to meet it, putting their own goals and local economies at risk.

The countries are very competitive in the business of data centers. Popular tax breaks: more than half of US states—including Arizona, New York, and Texas—offer operators some form of tax break, even special rates for land purchases and energy commitments. In Malaysia, Green Lane Pathway programs speed up construction approvals, cutting through red tape to expedite construction—and wiring—of data centers. Consent to data laws is to allow information to flow freely.

This interaction between watts and algorithms is redrawing the global impact map. It’s a change as profound as the oil boom of the 20th century, but it’s much less visible. No pipes are being built, no tanks are being replaced. Instead, non-documentary repositories humming with servers are becoming the hot spots of the world.

The extent to which this changes global influence is unclear. The real research on AI—where breakthroughs happen—will reside in research centers in San Francisco, London, Beijing, and Paris. Data centers that bring these algorithms to market, however, will be a low-cost, high-volume and low-cost business.

This electro-diplomacy will be an important pillar in the next few years. Measuring AI is less about algorithms and more about electronics.

However, nations that spend money at this moment should be careful; their advantage may seem fleeting as the booming economy finds a way to bring cheap, clean energy online at prices high enough to encourage home hosting.

For today’s power-rich providers of AI data centers, the challenge lies in turning this fleeting advantage into a sustainable edge. They will need to go beyond attracting data centers to build their own sustainable new systems that can thrive long after the “power rush subsides”.