Operationalizing Enterprise AI Adoption: A Comparative View of Cloud Hyperscalers’ Stack Readiness

Enterprise AI is transitioning from experimentation to scaled deployment, as organizations focus on operationalizing AI through integrated technology stacks. As AI adoption deepens across business functions, enterprises are demanding comprehensive infrastructure and platform capabilities that support training, orchestration, governance, and responsible deployment. Hyperscalers, including AWS, Microsoft Azure, and Google Cloud, are enabling this transformation, offering cohesive service stacks to support enterprise-grade AI. Their AI stacks influence how effectively enterprises can govern data, operationalize models, automate workflows, optimize costs, and integrate AI into production.

This report benchmarks hyperscaler AI-stack maturity across four core layers: infrastructure, data, model, and platform. It evaluates each hyperscaler on key dimensions, providing a structured framework to assess enterprise readiness. The findings help enterprises make informed decisions about provider alignment, identify gaps, and shape strategic investments in AI infrastructure. For technology leaders, the report delivers actionable insights to navigate evolving AI demands with speed, trust, and scalability.