The impact of AI on hardware and datacenters

Most discussions about AI focus on models, tools, and applications. But in practice, the impact of AI starts much lower in the stack — with infrastructure. Servers, storage, networks, and data centers are under growing pressure as AI workloads scale. These systems require more power, more cooling, faster data movement, and larger storage capacities than traditional workloads. Let's take a practical view of how AI is influencing hardware today: the challenges teams face, the technology shifts already happening, and what will likely shape infrastructure decisions in the next three to five years.