Global spending on cloud infrastructure continued its rapid ascent at the end of 2025, as new data from Omdia indicates that cloud infrastructure services reached $110.9 billion in the fourth quarter, marking a 29% increase from the same period a year earlier.
The remarkable growth extends a sustained expansion streak, with the market posting gains above 20% for six consecutive quarters. The acceleration reflects the fact that enterprise AI initiatives are moving out of trial phases and into real-world deployment.
The Rise of AI Agents
Where earlier waves of AI adoption focused heavily on specialized processors, companies are now requiring a wider range of infrastructure resources. Compute, storage, and networking capacity are all seeing increased pressure as companies build systems designed to support more complex, integrated AI workloads.
Part of this transformation is the rise of AI agents. These systems require not only raw computing power but also environments that can coordinate processes and maintain reliability at scale. As a result, cloud platforms are becoming even more deeply embedded in enterprise operations, serving as the backbone for both traditional applications and emerging AI services.
The three leading cloud providers all reported strong performance in the quarter, though growth rates varied. AWS retained its market lead with a 32% share and year-on-year growth of 24%. Microsoft Azure, with a 22% share, expanded by 39%, while Google Cloud posted the fastest growth at 50%, increasing its share to 12%.
Supporting the growth figures lies an unprecedented wave of capital investment. Hyperscalers are committing vast sums to expand data center capacity and support AI workloads. Amazon is projecting capital expenditures of roughly $200 billion in 2026, a significant increase from the previous year. Microsoft’s quarterly spending has also climbed sharply, while Google has outlined plans to more than double its annual investment range.
Clearly, demand for AI infrastructure is not only strong but also persistent. All three providers reported expanding backlogs, suggesting that enterprise customers are making long-term commitments to cloud-based AI deployments.
Moving Up the Stack
Competition is also shifting up the stack. While early cloud battles centered on infrastructure capacity and access to AI models, attention is increasingly turning to how those capabilities are applied. Vendors are investing in tools that help enterprises deploy AI systems within existing workflows and orchestrate complex processes.
This emphasis reflects a key concern among enterprise buyers: integrating AI into real-world operations without disrupting existing systems. The ability to embed AI into business processes, and scale it reliably, has become a critical measure of value.
A large group of providers is investing to build new offerings aimed at bridging this gap. These include platforms for building and managing AI agents, expanded model ecosystems, and tools designed to automate aspects of cloud operations and application development. The goal is to move AI from isolated use cases into fully integrated, production-level environments.
Looking ahead, the growth trajectory appears set to continue. Forecasts suggest cloud infrastructure spending will rise by roughly 27% in 2026.
Cloud infrastructure has grown far from its roots as a delivery mechanism for computing resources. It is now the operational foundation for next-gen enterprise technology, one defined by AI systems that require ever-growing levels of investment.
