Growing AI Needs Advance Hybrid Multicloud Maturity – ISG – March 4, 2026.

Enterprises decisively advanced in 2025 from isolated AI pilots to mission-critical AI deployments across hybrid and multicloud environments, increasing demand for new cloud infrastructure and services, according to a new research report published today by Information Services Group (ISG), a global AI-centered technology research and advisory firm.

The 2025 ISG Provider Lens global Multi Public Cloud Solutions report finds that enterprises are modernizing legacy environments while building cloud-native architectures to support AI-enabled applications. This has sharpened their focus on cloud infrastructure strength, operational governance and cost management.

“AI is no longer an experimental capability for enterprises,” said Anay Nawathe, ISG cloud delivery lead for the Americas. “Organizations are integrating AI into essential workflows, which raises the bar for performance, reliability, security and financial control across complex hybrid environments.”

Enterprises are building digital services on a foundation of cloud-native architectures that incorporate microservices, containers and API-first platforms, the report says. This shift has led to faster application deployment, better scalability and consistent operations across hybrid and multicloud environments. Adoption metrics show enterprises are validating this approach, with the use of Kubernetes management platforms rising sharply and most organizations reporting tighter DevOps integration and more efficient resource use, ISG says.

Operational complexity is increasing as AI workloads, open-source components and distributed systems converge, the report says. Enterprises are responding by prioritizing integrated platforms that combine cloud security, observability, Kubernetes management and governance. These capabilities help organizations eliminate data silos, automate policy enforcement and maintain trust as AI pipelines extend across infrastructure layers, ISG says.

Financial governance has become a critical concern as AI workloads put sustained pressure on infrastructure budgets, the report says. Enterprises are adopting advanced FinOps practices to gain granular insight into compute, storage and network consumption, particularly for GPU-intensive training and inference. Organizations increasingly expect FinOps tools to integrate with security and observability data to provide proactive cost control and clearer measurement of business outcomes.

“Kubernetes and cloud-native platforms now form the backbone of scalable AI operations,” said Shashank Rajmane, principal analyst, ISG Provider Lens Research, and lead author of the report. “Enterprises need consistent control across environments, and service providers play a key role in helping them operationalize AI efficiently and securely.”

The report also explores other public cloud trends affecting enterprises, including enterprises’ growing acceptance of open-source tools and rising demand for AI-based enhancements to Kubernetes platforms.

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