The global cloud infrastructure market in Q3-2025 is dominated by a small group of hyperscalers as enterprise adoption of artificial intelligence accelerates.
Amazon Web Services, Microsoft Azure, and Google Cloud collectively account for the majority of global cloud spending, with growth increasingly driven by production-scale AI workloads, multi-model platforms, and agent-based enterprise applications.
Amazon Web Services Leads Global Cloud Market
Amazon Web Services retained its position as the world’s largest cloud infrastructure provider in Q3 2025, holding a 32 percent market share and delivering 20 percent year-on-year revenue growth. AWS benefited from easing compute supply constraints and rising incremental demand linked to its strategic partnership with Anthropic, according to the latest Omdia report.
By the end of Q3, AWS reported a total backlog of $200 billion, highlighting strong long-term demand visibility across enterprise and public sector customers. Amazon Bedrock continued to expand rapidly, strengthening AWS’s position as a multi-model AI platform. The service now supports Claude 4.5, 18 managed open-weight models, and enhanced Guardrails and Data Automation capabilities designed to support enterprise governance and scalable AI deployment.
At AWS re:Invent 2025, the company introduced the Nova 2 model family, along with Nova Act and Nova Forge, reinforcing its end-to-end enterprise AI portfolio spanning foundation models, agents, and automation. AWS also expanded its global infrastructure footprint with the launch of the AWS Asia Pacific New Zealand Region in September, adding three availability zones to support data residency requirements and low-latency workloads.
Microsoft Azure Strengthens Second Position
Microsoft Azure remained the second-largest cloud provider globally in Q3 2025, with a 22 percent market share and strong 40 percent year-on-year revenue growth. Azure’s performance was underpinned by rising enterprise AI deployments and deeper integration with Microsoft’s broader software ecosystem.
In October, Microsoft renewed its partnership with OpenAI, cementing Azure as the primary platform for OpenAI’s AI development and deployment. Azure AI Foundry continued to expand its model ecosystem, supporting frontier foundation models such as Claude Opus 4.5, Claude Sonnet 4.5, and Haiku 4.5. The platform now serves more than 80,000 customers and provides access to over 11,000 models.
Microsoft also introduced the Microsoft Agent Framework in October, enabling enterprises to build and orchestrate multi-agent systems. Organizations such as KPMG are already using the framework to enhance audit processes, with these production-grade AI applications contributing to Azure’s overall growth momentum. Alongside platform innovation, Microsoft continued to invest heavily in regional infrastructure, announcing plans to expand its Azure cloud region in Malaysia and to launch a new Azure datacenter region in India in 2026.
Google Cloud Gains Share on Enterprise AI Demand
Google Cloud remained the third-largest cloud services provider in Q3 2025, increasing its market share to 11 percent and delivering 36 percent year-on-year growth. The company’s expansion was driven primarily by enterprise AI offerings, with quarterly revenue from this segment reaching several billion dollars.
Google Cloud reported a backlog of $157.7 billion as of September 30, up sharply from $108.2 billion in the previous quarter, signaling improving demand visibility and longer-term customer commitments. Vertex AI’s Model Garden continued to broaden its portfolio, adding multimodal models from the Gemini 2.5 series, Kimi K2 Thinking, and DeepSeek-V3.2 to support diverse enterprise use cases.
In October 2025, Google Cloud also launched Gemini Enterprise, an AI platform tailored for business customers. The platform integrates the Gemini model family with enterprise-grade AI agents, no-code development tools, and built-in security and governance features, positioning Google Cloud to compete more aggressively for large-scale enterprise AI deployments.
Global Cloud Infrastructure Spending Hits $102.6 Billion
Global spending on cloud infrastructure services reached $102.6 billion in the third quarter of 2025, registering 25 percent year-on-year growth, according to new research from Omdia. The market has now delivered growth above 20 percent for five consecutive quarters, underlining sustained demand and structural strength across the cloud sector.
Omdia notes that this momentum reflects a deeper shift in enterprise technology strategies. Demand for artificial intelligence is moving decisively beyond early experimentation and pilot projects toward scaled, production-grade deployment. As this transition accelerates, competition among hyperscalers is increasingly shifting away from marginal gains in model performance and toward platform-level capabilities that enable multi-model deployment and reliable operation of AI agents in real-world environments.
Hyperscalers Maintain Dominance
In Q3 2025, Amazon Web Services, Microsoft Azure, and Google Cloud retained their market rankings from the previous quarter. Together, the three hyperscalers accounted for 66 percent of global cloud infrastructure spending and delivered combined year-on-year growth of 29 percent.
AWS recorded a notable reacceleration in growth, expanding 20 percent year on year in Q3 2025. This marked the company’s strongest quarterly growth performance since 2022. Microsoft Azure and Google Cloud continued to outperform the broader market, each posting year-on-year growth of more than 35 percent, supported by rising enterprise AI workloads and expanding platform adoption.
Omdia highlighted that backlog levels among leading cloud providers continued to rise during the quarter. AWS, Microsoft, and Google Cloud all reported further increases in order backlogs, reinforcing confidence in the resilience of underlying demand and the long-term growth trajectory of the cloud infrastructure market.
From AI Experiments to Production Platforms
As enterprise AI demand matures, cloud growth is increasingly driven by the deployment of enterprise-grade applications rather than proof-of-concept initiatives. Hyperscalers are adapting their AI strategies accordingly, placing greater emphasis on production readiness, operational reliability, and platform depth.
Enterprises are no longer evaluating AI platforms solely on the strength of individual models. Instead, they are prioritizing support for multi-model strategies, agent-based applications, and deployment flexibility across diverse workloads. This shift is accelerating investments in platform-level AI capabilities across the major cloud providers.
AWS, Microsoft Azure, and Google Cloud are integrating proprietary foundation models with a growing portfolio of third-party and open-weight models. Managed AI platforms such as Amazon Bedrock, Azure AI Foundry, and Vertex AI Model Garden are playing a central role in enabling multi-model adoption at scale.
“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.”
Rising Focus on AI Agents
Omdia also points to growing investment in agent build-and-run capabilities as hyperscalers respond to the complexity of real-world AI deployment. While early experimentation demonstrated potential, many enterprises still struggle with standardization, governance, and operational continuity when deploying AI agents in production environments.
“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.”
RAJANI BABURAJAN
