Enterprises around the world moved decisively in 2025 from experimenting with artificial intelligence to embedding it into core business operations, driving a sharp increase in demand for robust cloud infrastructure and advanced management services. That shift is detailed in a new research report released today by Information Services Group (ISG), a global AI-focused technology research and advisory firm.
ISG examined how organizations are deploying AI across hybrid and multicloud environments and what that means for cloud strategy going forward.
According to the 2025 ISG Provider Lens global Multi Public Cloud Solutions report, companies are no longer treating AI as a collection of isolated pilots. Instead, AI-enabled applications are being rolled out across mission-critical workflows, forcing enterprises to modernize legacy systems while building cloud-native foundations capable of scaling securely and cost-effectively. This transition has heightened attention on infrastructure resilience, operational governance, and financial discipline as AI workloads stretch traditional IT models.
ISG notes that enterprises are increasingly standardizing on cloud-native architectures built around microservices, containers, and API-first design principles. These approaches allow applications to be deployed and updated more quickly while maintaining consistency across on-premises, private cloud, and public cloud environments. The report points to strong adoption metrics, including a significant rise in the use of Kubernetes management platforms and tighter integration between development and operations teams. Organizations report improved resource utilization and faster time to market as a result.
As AI pipelines grow more complex, however, operational challenges are intensifying. Distributed systems, open-source components, and data-intensive AI workloads are converging across multiple environments, increasing the risk of blind spots and policy gaps. In response, enterprises are prioritizing integrated cloud platforms that bring together security, observability, Kubernetes management, and governance. ISG says these consolidated approaches help eliminate data silos, automate compliance, and preserve trust as AI systems span infrastructure layers and geographies.
FinOps Capabilities
Cost management has emerged as another defining concern. AI training and inference, particularly for GPU-heavy workloads, are placing sustained pressure on cloud budgets. The report finds that enterprises are accelerating adoption of advanced FinOps practices to gain detailed visibility into consumption patterns across compute, storage, and networking. Increasingly, organizations expect FinOps capabilities to integrate with security and observability tools, enabling proactive cost controls and clearer links between spending and business outcomes.
“AI is no longer an experimental capability for enterprises,” said Anay Nawathe, ISG’s 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.”
ISG also emphasizes the growing role of service providers in helping enterprises operationalize AI at scale. Providers are expected to deliver not just infrastructure, but also governance frameworks, automation, and expertise that allow organizations to manage AI workloads consistently across diverse platforms. As cloud-native and Kubernetes-based environments become the backbone of enterprise AI, the ability to maintain control without sacrificing agility is becoming a competitive differentiator.
Executive Insights FAQ
Why did enterprise AI adoption accelerate in 2025?
Organizations moved beyond pilots as AI matured into a practical tool for core workflows and competitive advantage.
How are enterprises supporting AI at scale?
By modernizing legacy systems and adopting cloud-native architectures across hybrid and multicloud environments.
What operational challenges are emerging?
Increased complexity from distributed systems and AI pipelines is driving demand for integrated security and governance platforms.
Why is FinOps becoming critical?
AI workloads, especially GPU-intensive ones, are increasing infrastructure costs and require tighter financial control.
What role do service providers play?
They help enterprises manage, secure, and optimize AI-enabled cloud environments efficiently and consistently.
