Omdia: Global cloud infrastructure spending hits $102.6 billion

Global spending on cloud infrastructure services reached $102.6 billion in Q3 2025, representing 25% year-on-year growth, according to research from London-based Omdia. Market momentum remained stable, marking the fifth consecutive quarter in which growth has remained above 20%, highlighting continued strength across the sector. This performance reflects a significant shift in the technology landscape as enterprise demand for AI moves beyond early experimentation toward scaled production deployment. As this transition accelerates, hyperscalers are increasingly redirecting competition away from the incremental gains in model performance and toward platform-level capabilities that support multi-model deployment and ensure the reliable operation of AI agents in real-world environments.

In Q3 2025, AWS, Microsoft Azure, and Google Cloud maintained their market rankings from the previous quarter, collectively accounting for 66% of global cloud infrastructure spending. Together, the three hyperscalers delivered 29% year-on-year growth.

AWS’s growth reaccelerated to 20% year on year quartering Q3 2025, marking its strongest performance since 2022. Microsoft Azure and Google Cloud also maintained strong momentum, each delivering year-on-year growth of more than 35%. As enterprise demand for AI continues to materialize, growth in the cloud market is shifting from early-stage experimentation and pilot projects toward the scaled deployment of enterprise-grade AI applications. Backlog levels among leading cloud providers continued to rise, with AWS, Microsoft, and Google Cloud all reporting further increases in Q3 order backlogs, reinforcing the market’s underlying resilience and healthy demand environment.

Hyperscalers’ AI strategies are evolving from a primary focus on incremental model performance toward more platform-driven and production-ready approaches, according to the report. Enterprises are no longer evaluating AI platforms solely on model capabilities, but increasingly on their support for multi-model strategies and agent-based applications.

This shift is accelerating hyperscalers’ move toward platform-level AI capabilities. AWS, Microsoft Azure, and Google Cloud are integrating proprietary foundation models with a growing range of third-party and open-weight models, leveraging managed AI platforms and services such as Amazon Bedrock, Azure AI Foundry, and Vertex AI’s Model Garden to expand support for multi-model adoption.

“Collaboration across the ecosystem remains critical,” said Rachel Brindley, Senior Director at Omdia. “Multi-model support is increasingly viewed as a production requirement rather than a feature, as enterprises seek resilience, cost control, and deployment flexibility across generative AI workloads.”

Meanwhile, hyperscalers are stepping up investment in agent build-and-run capabilities, as real-world deployment continues to prove more complex than early experimentation suggested. “Many enterprises still lack standardized building blocks that can support business continuity, customer experience, and compliance at the same time, which is slowing the real-world deployment of AI agents,” said Yi Zhang, Senior Analyst at Omdia. “This is where hyperscalers are increasingly stepping in, using platform-led approaches to make it easier for enterprises to build and run agents in production environments.”

Channel Impact^®
The data reinforce the trend toward cloud migration and the channel’s continuing business opportunity in assisting with the transitions.