Cloud Infrastructure Spending Hits $102.6 Billion in Q3 2025
Global spending on cloud infrastructure services surged to $102.6 billion in the third quarter of 2025, according to research from Omdia. This figure represents a substantial increase of 25% year-on-year and marks the fifth consecutive quarter of growth exceeding 20%. This trend is driven largely by a heightened enterprise demand for artificial intelligence (AI), which is transitioning from initial testing phases to full production deployment.
The major players in the cloud market maintained their positions. Amazon Web Services (AWS), Microsoft Azure, and Google Cloud collectively accounted for 66% of total spending in the sector. The three companies achieved a combined growth rate of 29% year-on-year. AWS reported a notable revenue growth of 20%, its strongest performance since 2022, and held a market share of 32%. Omdia attributes this uptick to a reduction in compute supply constraints and increasing demand, particularly influenced by AWS’s partnership with Anthropic.
Microsoft Azure, the second-largest cloud provider, maintained a 22% market share while experiencing a remarkable 40% year-on-year revenue growth. Google Cloud also recorded significant progress, achieving a 36% increase in revenue compared to the previous year, thereby raising its market share to 11%, primarily due to its enterprise AI offerings.
Backlogs and Investment Trends
Backlogs among leading cloud providers have continued to grow, with all three companies reporting increases during the third quarter. AWS noted a total backlog of $200 billion by the end of the quarter, while Google Cloud’s backlog surged to $157.7 billion, a sharp rise from $108.2 billion in the second quarter of 2025.
Omdia highlighted that as enterprises seek to enhance their AI capabilities, hyperscalers are shifting towards platform-level AI strategies. AWS, Microsoft Azure, and Google Cloud are integrating proprietary foundation models alongside a broader range of third-party and open-weight models. This strategy focuses on leveraging managed platforms and services such as Amazon Bedrock, Azure AI Foundry, and Vertex AI’s Model Garden to expand their support for customers.
Rachel Brindley, senior director at Omdia, emphasized the importance of collaboration across the cloud ecosystem, stating, “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.”
Challenges in Real-World Deployment
Despite the optimistic growth figures, many organizations are still grappling with real-world deployment of AI technologies. Omdia has noted that hyperscalers are increasing investments in agent build-and-run capabilities to address these challenges. Recent initiatives include AWS AgentCore and Microsoft’s Agent Framework, which aim to provide standardized foundational capabilities to help businesses build, deploy, and operate AI agents more effectively in production environments.
Yi Zhang, senior analyst at Omdia, pointed out the hurdles many enterprises face: “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.” Zhang added that hyperscalers are stepping in to facilitate easier construction and operation of agents in production settings through platform-led approaches.
As the demand for cloud services continues to rise, the industry appears poised for further growth, with ongoing investments aimed at overcoming deployment challenges and enhancing AI capabilities across various sectors.
