AI INFRASTRUCTURE
The AI revolution has hit a wall – and it’ s made of power cables and server racks. While tech giants pour billions into data centres and enterprises launch endless pilot projects, a peculiar paradox is emerging.
We’ re building the most powerful computational infrastructure in human history, yet somehow most companies can’ t figure out how to actually use it. Goldman Sachs research predicts that global data centres will consume 165 % more electricity by 2030.
Meanwhile, Accenture finds that only 8 % of enterprises have managed to scale AI projects beyond the pilot stage.
The future challenges of AI infrastructure Current data centres consume around 55GW of electricity globally. Today, business applications like email consume about a third of that power, while AI workloads account for just 14 %.
But Goldman Sachs expects this picture to flip dramatically by 2027, with total consumption jumping to 84GW and AI claiming more than a quarter of all power usage. A single ChatGPT query burns through 2.9 watt-hours of electricity – nearly ten times what a Google search requires.
Where traditional cloud server racks might be less hungry for power, their AI equivalents are hungrier, consuming ten times as much electricity due to the intensive requirements of training and running machine learning( ML) models. Europe faces a particularly daunting reality.
220 November 2025