According to an analysis from the BCG Institute, the artificial intelligence ecosystem will require about $2.6 trillion in annual end-market spending by 2030 to fund data centers, chips, model development and investor returns. Businesses would bear $1.8 trillion of that total, compared with $366 billion from consumers, $204 billion from hyperscalers and $200 billion for emerging technologies such as robotics and autonomous systems. The model includes data center operating costs, including power, chips and depreciation, as well as a 10% operating margin on external revenue earned by AI labs. The estimates exclude China and primarily cover infrastructure being built in the United States, where energy, permitting and supply chains will determine the pace of deployment. The shift from model training toward inference and effective chip utilization will be key indicators for determining whether commercial demand can justify these massive investments.
Source: Read the original article
