For years, the assumption around artificial intelligence infrastructure was that serious compute would be built in places where hyperscale cloud, developer density, and capital were already concentrated: Silicon Valley, Seattle, London, and a small number of other technology hubs.
There was a practical reason for these geographies. Training and deploying AI at scale requires data centers, compute, networking capacity, energy, and advanced infrastructure. Over time, that dependence has hardened into market concentration. Amazon, Microsoft, and Google together account for nearly two-thirds of global enterprise cloud infrastructure spending.
That earlier logic no longer holds. Compute is becoming more expensive, more power-intensive, and harder to access outside a small group of dominant providers. Builders are starting to confront questions like: Where will the power come from? Can chips be shipped to this jurisdiction? Whose laws apply to the data once it moves?
Those questions are increasingly being answered outside Silicon Valley.
What scarcity teaches
