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What are the risks associated with data centre growth?
11/6/2025
8 min read
Feature
Artificial intelligence (AI) demands large amounts of data and power. And the demand is rising. But what does this mean in terms of energy consumption? Where are the new data centres likely to be located, and what will be the associated costs and risks? These and other issues were addressed in the Aurora Energy Research spring forum held in London last month. New Energy World Features Editor Brian Davis reports on a keynote session, ‘Navigating data centre growth: Beyond the hype’, presented by Richard Howard, Global Research Director.
‘AI demand is becoming exponentially more data intensive and energy intensive’, noted Howard, of Aurora Energy Research. He sees the new model of AI doubling roughly every five months, with power demand climbing at a slightly lower (though still challenging rate) – doubling every year.
To put AI in context, he compared its computing power to the human brain. While the brain operates at 20 petaflops (equal to 20 x 1015 floating-point operations per second), AI operates a billion times faster, at 1024 flops. Developing an AI training model takes about four months at a constant load in excess of 100 MW. That totals more than 300 GWh with energy costs in the tens of millions of dollars. Development takes deep pockets, as an AI training model can cost billions of dollars.
Although data demand for AI is high and continuing to surge globally, Howard recognised that there is ‘a huge amount of uncertainty’ due to poor public data with different methodologies and other factors at play. The estimates of current power demand by AI vary from 500–700 TWh, which is roughly the power consumed by Germany, Canada and Brazil together.