The Infrastructure Thesis

  In many technology cycles, spending rises quickly and then falls just as fast. Companies invest aggressively during boom periods, but when demand slows, capital spending is often cut. AI infrastructure is different. AI capital expenditure tends to be sticky. Once companies begin investing in AI infrastructure, it becomes difficult to stop. The reason is structural. Building AI infrastructure requires long-term commitments. Data centers must be constructed. Power capacity must be secured. Cooling systems must be installed. Networking equipment must be deployed. These projects require billions of dollars and often take years to complete. Once the process begins, companies rarely cancel halfway. Instead, spending continues even if short-term demand fluctuates. This is why AI infrastructure investment behaves differently from traditional technology spending. In a typical tech cycle, companies can reduce spending quickly by delaying software projects or cutting marketing budgets. Infr...