REDWOOD CITY, Calif. – According to a recently published report from Dell’Oro Group, a source for market information about the telecommunications, networks and data center industries, the multiyear artificial intelligence expansion cycle is projected to drive worldwide data center capital expenditures to $1.7 trillion by 2030. 

Hyperscale and neo cloud service providers, along with sovereign AI initiatives, are entering a new phase of infrastructure expansion.

“The top four U.S. hyperscale cloud service providers – Amazon, Google, Meta and Microsoft – entered 2026 with strong momentum, raising combined data center capital expenditures to nearly $600 billion,” said Baron Fung, senior research director at Dell’Oro Group. “Despite increased scrutiny around AI infrastructure returns, hyperscalers continue to invest aggressively, supported by large cash reserves and a long-term focus on market share. This growth is being driven by the deployment of larger and more complex AI clusters, which are increasing demand for high-performance networking, storage, inference capacity and advanced power and cooling infrastructure.”

In addition to the top hyperscale cloud service providers, “AI model builders, neo cloud providers and sovereign cloud initiatives are accelerating their own data center deployments,” Fung added. “As a result, global data center [capital expenditures] is expected to approach $1 trillion in 2026, reaching a major industry milestone sooner than anticipated.”

Additional highlights from the Data Center IT Capex 5-Year Forecast Report include:

  • Accelerated servers for AI training and domain-specific workloads could account for approximately two-thirds of total data center infrastructure spending by 2030.
  • While the top four U.S. hyperscalers are expected to represent about half of global data center capital expenditures by 2030, emerging AI model builders and neo cloud service providers are projected to grow at significant rates.
  • Outside hyperscale, enterprise data center investment remains constrained by tariffs, monetary policy and uncertain AI returns.