AI Infrastructure Expands Beyond GPUs: Enterprises Demand Full-Stack Solutions for Scalable Growth

March 26, 2026
AI Infrastructure Expands Beyond GPUs: Enterprises Demand Full-Stack Solutions for Scalable Growth
  • The AI adoption trend is expanding beyond GPUs to include CPUs, storage, and networking, with vendors prioritizing governance, workflow orchestration, and deployment tools to scale AI from pilots to production.

  • Demand now spans the full stack—from GPUs to CPUs, storage, and networking—as enterprises build more complex, scalable, and governable AI environments that can run in production.

  • Industry observers say the shift requires robust toolchains for governance, orchestration, and deployment to translate AI pilots into scalable, enterprise-ready systems.

  • Cloud infrastructure services are defined as BMaaS, IaaS, PaaS, CaaS, and serverless offerings hosted by third-party providers and accessed over the Internet.

  • Omdia defines cloud infrastructure services as the combined family of BMaaS, IaaS, PaaS, CaaS, and serverless services delivered by external providers online.

  • Microsoft and Google are expanding AI model capabilities and agent-focused features, with Microsoft extending agent capabilities into cloud operations and modernization, and Google boosting Vertex AI with Gemini models for enterprise-grade readiness.

  • Cloud vendors face growing pressure to differentiate amid rising AI workloads and demand for scalable, reliable infrastructure.

  • Backlogs at AWS, Microsoft, and Google Cloud indicate ongoing enterprise AI investment, with hyperscalers accelerating capital expenditure to expand AI infrastructure.

  • AWS led Q4 2025 with a 32% market share and a large backlog, while signaling new agent-oriented offerings and proprietary data support for early training of Amazon Nova models.

  • Global cloud infrastructure market reached about $110.9 billion in Q4 2025, up 29% year over year, driven by AI-related demand.

  • Providers are expanding agent-focused offerings and strengthening orchestration, governance, deployment capabilities, and AI-enabled workflows across cloud operations and development.

  • Enterprises want AI capabilities that integrate smoothly into existing workflows and data environments without disrupting ongoing operations.

Summary based on 5 sources


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