The $700B AI Infrastructure Race

Why $700 Billion? The Forces Driving the SpendThe spending surge is driven by a single reality: demand for AI compute is outstripping supply across every major cloud provider. Inference workloads — running trained AI models to serve predictions, generate text, and produce images — now account for an estimated 60 to 70 percent of total AI compute demand across major hyperscalers, up from roughly 40 percent in 2024.2 As enterprises adopt AI agents, copilots, and multimodal applications, the compute requirements are scaling faster than anyone anticipated.Every major cloud provider reported in their most recent earnings calls that they are "capacity-constrained" — they have more customer demand than they can serve. This is the core justification for the spending: it is not speculative building, but building to meet contractual backlogs worth hundreds of billions of dollars.