In the initial years of multicloud adoption, enterprises took cautious, calculated steps to build and manage infrastructures that spanned multiple cloud providers. The objective was flexibility, performance optimization, and risk mitigation. Yet, in 2025, enterprises are struggling more than ever to operate effective multicloud environments. Why? The rapid movement toward AI systems, combined with a lack of thoughtful planning, has overwhelmed management strategies and pushed many organizations to the brink of multicloud madness.
The integration of AI-driven workloads into enterprise cloud strategies has become a dominant force shaping cloud investment and architecture decisions. However, most businesses underestimate the complexity this adds. In particular, the introduction of GPU-focused cloud providers, such as CoreWeave and others, has dramatically altered the landscape. These clouds promise specialized performance for AI workloads but operate with unique requirements that many enterprises are unprepared to handle.
Moving to AI systems without a plan
The surge in AI adoption brought many transformative benefits: smarter decision-making, automation, personalized customer experiences, and competitive differentiation. However, enterprises are implementing AI systems without understanding how these technologies integrate into existing multicloud strategies. Here are five of the most significant challenges:
