Enterprise AI Moves From Experimentation to Mission-Critical Production
The artificial intelligence landscape shifted decisively in 2025. What began as scattered pilot programs has evolved into production-grade AI deployments that power essential business operations. According to ISG’s 2025 Provider Lens® global Multi Public Cloud Solutions report, enterprises are no longer treating AI as a experimental technology—they’re embedding it into workflows that directly impact revenue, customer experience, and competitive positioning.
This transition from proof-of-concept to production scale has exposed critical infrastructure gaps. Legacy systems built for traditional workloads cannot support the computational intensity, data velocity, and distributed architecture that modern AI applications demand. Organizations are responding by fundamentally rearchitecting their cloud environments, prioritizing platforms that deliver unified security, observability, and financial governance across hybrid and multicloud landscapes.
“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.”
Cloud-Native Architecture Becomes the Foundation for Scalable AI
Enterprises are rebuilding their digital infrastructure on cloud-native principles—microservices, containerization, and API-first platforms. This architectural shift delivers tangible operational benefits: faster application deployment cycles, elastic scalability that matches workload fluctuations, and operational consistency regardless of whether resources run on-premises or across multiple public clouds.
The data validates this strategic direction. Kubernetes management platform adoption has accelerated sharply, with most organizations reporting tighter DevOps integration and measurably improved resource utilization. These platforms provide the orchestration layer necessary to manage distributed AI workloads that span edge devices, private data centers, and public cloud regions.
Complexity Drives Demand for Unified Governance Platforms
As AI workloads intersect with open-source components and distributed systems, operational complexity multiplies. Enterprises face the challenge of maintaining visibility, enforcing consistent policies, and ensuring security across infrastructure layers that were never designed to work together seamlessly.
Organizations are addressing this challenge by consolidating onto integrated platforms that combine cloud security, observability, Kubernetes management, and governance capabilities. This convergence eliminates data silos, enables automated policy enforcement, and maintains trust as AI pipelines extend across increasingly heterogeneous infrastructure. The ISG report evaluated 77 providers across these critical capability areas, naming Broadcom as a Leader in three quadrants, with Dynatrace and IBM achieving Leader status in two quadrants each.
FinOps Emerges as Critical Discipline for AI Cost Management
Financial governance has become urgent as GPU-intensive training and inference workloads place sustained pressure on infrastructure budgets. Enterprises are adopting advanced FinOps practices to gain granular visibility into compute, storage, and network consumption. This visibility enables proactive cost control rather than reactive budget management.
Organizations increasingly expect FinOps platforms to integrate with security and observability data, creating a unified view that connects infrastructure spending to business outcomes. This integration allows finance and technology teams to make informed tradeoffs between performance requirements and budget constraints.
“Kubernetes and cloud-native platforms now form the backbone of scalable AI operations,” said Shashank Rajmane, principal analyst at ISG 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 ISG research also highlights rising acceptance of open-source tools and growing demand for AI-enhanced Kubernetes capabilities—trends that will further reshape the multicloud landscape as enterprises scale their AI ambitions.
About ISG Provider Lens® Research
The ISG Provider Lens® Quadrant research series is the only service provider evaluation of its kind to combine empirical, data-driven research and market analysis with the real-world experience and observations of ISG’s global advisory team. Enterprises will find a wealth of detailed data and market analysis to help guide their selection of appropriate sourcing partners, while ISG advisors use the reports to validate their own market knowledge and make recommendations to ISG’s enterprise clients. The research currently covers providers offering their services globally, across Europe, as well as in the U.S., Canada, Mexico, Brazil, the U.K., France, Benelux, Germany, Switzerland, the Nordics, Australia and Singapore/Malaysia, with additional markets to be added in the future. For more information about ISG Provider Lens research, please visit this webpage.
About ISG
ISG (Nasdaq: III) is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world’s top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data, in-depth knowledge of provider ecosystems, and the expertise of its 1,600 professionals worldwide working together to help clients maximize the value of their technology investments.
