Enterprises made a decisive leap in 2025, moving beyond limited AI pilot projects to deploying artificial intelligence at a mission-critical scale across hybrid and multicloud environments. According to a newly released research report from Information Services Group (ISG), this rapid evolution is significantly increasing demand for advanced cloud infrastructure and specialized cloud services worldwide.

Rather than treating AI as an experimental add-on, organizations are now embedding it directly into core business workflows. As a result, enterprises are placing far greater emphasis on performance, reliability, security, and financial governance within increasingly complex IT environments. This shift marks a fundamental change in how businesses view and operationalize AI.

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The 2025 ISG Provider Lens global Multi Public Cloud Solutions report reveals that enterprises are simultaneously modernizing legacy systems and building cloud-native architectures designed to support AI-driven applications. Consequently, cloud infrastructure resilience, operational governance, and cost optimization have emerged as top strategic priorities for IT leaders.

“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.”

Moreover, the report highlights that enterprises are increasingly developing digital services using cloud-native foundations built on microservices, containers, and API-first platforms. This architectural shift is enabling faster application deployment, improved scalability, and more consistent operations across hybrid and multicloud setups. Supporting this trend, adoption metrics indicate a sharp rise in the use of Kubernetes management platforms. At the same time, most organizations report stronger DevOps integration and more efficient utilization of infrastructure resources.

However, as AI workloads expand, operational complexity continues to grow. The convergence of AI models, open-source technologies, and distributed systems is prompting enterprises to seek integrated platforms that unify cloud security, observability, Kubernetes management, and governance. These integrated solutions help organizations break down data silos, automate policy enforcement, and maintain trust as AI pipelines span multiple infrastructure layers.

In addition, financial governance has become a critical concern. AI workloads especially those requiring GPU-intensive training and inference are placing sustained pressure on cloud budgets. To address this, enterprises are increasingly adopting advanced FinOps practices that deliver granular visibility into compute, storage, and network consumption. Organizations now expect FinOps tools to integrate seamlessly with security and observability platforms, enabling proactive cost control and clearer alignment between spending and business outcomes.

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“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.”

Beyond AI infrastructure, the report also examines broader public cloud trends, including enterprises’ growing acceptance of open-source tools and increasing demand for AI-powered enhancements within Kubernetes platforms. Additionally, ISG evaluated 77 providers across four key quadrants FinOps Platforms, Observability Platforms, Security Platforms, and Kubernetes Management Platforms recognizing multiple industry leaders for their capabilities in supporting modern, AI-driven cloud environments.

Overall, the findings underscore how AI has become a central force reshaping enterprise cloud strategies, accelerating innovation while redefining operational and financial expectations across hybrid and multicloud ecosystems.

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