AI is increasing density, power demand and complexity. Most data centers are not designed to support it. Understand where your infrastructure stands and what needs to change.
AI workloads are redefining how data centers are built and operated. Demand is rising faster than capacity. At the same time, operators are expected to deploy faster and maintain uptime in more complex environments.
What worked for traditional workloads is no longer sufficient.
Most strategies focus on scaling compute but the real limitation is infrastructure. A significant portion of space is still allocated to non-core systems. Infrastructure inefficiencies limit how much compute can actually be deployed. This creates a gap between what your data center can support and what AI requires.
This gap typically shows up in:
These challenges are interconnected and compound over time.
Supporting AI workloads requires a different infrastructure model:
Download the framework
This will help you understand how infrastructure impacts performance, efficiency, scalability, and the questions you must ask before you start.

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