University of Kwazulu-Natal

Ai Workloads Are Surging Is Your Infrastructure Ready Wsj

Bonisiwe Shabane
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ai workloads are surging is your infrastructure ready wsj

The generative AI boom is disrupting the economics of computing—not just in terms of how much energy is consumed, but also in where and how systems are built. Over decades, cloud infrastructure evolved to support web hosting, email and enterprise apps. But AI workloads are something different: much larger, more power-hungry and far less forgiving of inefficiencies. As a result, traditional data centers are reaching their limits. Training and running AI models at scale require high-throughput interconnects, purpose-built chips and energy-efficient systems capable of handling concentrated power loads. The International Energy Agency projects that AI-related electricity consumption will rise from roughly 8 TWh in 2023 to at least 85 TWh by 2026—an order-of-magnitude jump.

To put that in perspective, a single 100-MW hyperscale data center operating at near full load can consume about 876 GWh per year, roughly the electricity used by 83,000 average U.S. homes. To meet this demand, cloud providers are re-engineering everything from processor designs to cooling systems. What’s emerging is a shift toward AI-native infrastructure built on an industrial scale. In the process, these providers are charting new territory—not simply upgrading what exists, but inventing what comes next. In other words, the cloud is no longer a utility—it’s a strategic lever.

Therefore, competing in the AI era means understanding the infrastructure that powers it. The rapid re-engineering of cloud infrastructure isn’t a theoretical bet; it’s a response to tangible, widespread demand. Today’s use cases cut across industries and customer types. Whether through delivering faster results to users, accelerating scientific breakthroughs or lowering infrastructure costs, AI is becoming a foundational layer of business operations. And the infrastructure of the cloud is the first to match this shift. The hyperscalers powering the AI transformation—AWS, Google Cloud, Microsoft Azure—are now among the world’s largest investors in custom-built infrastructure, retooling the cloud first to scale, and second in order to specialize.

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