Every transformative technology eventually runs into the same contradiction: its potential outpaces the infrastructure built to support it. Artificial intelligence (AI) is now at that point. Its ability to transform how we work, discover, create, and solve problems could benefit virtually every part of the world, yet the physical systems required to sustain its extraordinary computational demands are still catching up. The gap is particularly visible in energy. More than 666 million people worldwide still lack access to electricity, while the energy infrastructure supporting today’s technology ecosystem is under pressure. Data centres consumed around 415 TWh of electricity globally in 2024, and the International Energy Agency (IEA) expects that demand to more than double by 2030, reaching roughly 945 TWh. The infrastructure that was sufficient for today’s computing is, therefore, being asked to support a radically different scale of computation.
AI’s ambitions demand a corresponding leap in the energy infrastructure that powers it. Expanding data centre capacity without strengthening energy generation, transmission, storage, and grid resilience risks further pressuring systems that businesses and communities already depend on. Energy capacity and efficiency must, therefore, be integral to AI’s growth, not considerations addressed after the computing infrastructure is built.
