The Silent Risk Behind AI Growth — Our Power Grid Isn’t Ready
Artificial Intelligence is now deeply embedded in our lives. From personalised recommendations and fraud detection to real-time customer support and predictive maintenance, it’s powering how industries innovate and operate.
But as AI becomes more capable, it also becomes more demanding—especially when it comes to energy.
We often talk about faster chips, better models, and smarter data pipelines. But what’s less discussed is the simple truth: all of this runs on power. And our existing power grid wasn’t built for what’s coming.
AI workloads—especially training and running large models—consume exponentially more energy than traditional computing tasks. According to the International Energy Agency, data centre energy demand could triple by 2030, driven in large part by AI.
At the same time, the infrastructure that powers AI—the electrical grid—is showing signs of serious strain. We’re already seeing rolling blackouts during summer heatwaves, stalled data centre projects due to grid capacity constraints, and urgent warnings from utilities worldwide.
For too long, organisations have assumed that if you can pay for power, you can get it. That assumption is no longer reliable.
Why This Matters
The next bottleneck in AI adoption won’t be compute power or data availability—it will be energy. Those who ignore this risk may find themselves unable to scale. Those who plan for it will build a lasting advantage.
Takeaway: We’re building the AI economy on a 20th-century energy foundation. It’s time to stop thinking of energy as an afterthought and start treating it as a strategic enabler.
