The shift from AI training to inference is fundamentally changing how data centers operate. Rather than supporting periodic, centralized workloads, operators are now managing continuous, latency sensitive AI applications across increasingly distributed environments. This evolution is placing new demands on power, cooling, capacity planning, and operational resilience, making infrastructure visibility more critical than ever.
Traditional approaches to infrastructure management are struggling to keep pace with dynamic AI workloads, where real time operational insight is essential to optimize available power, respond to changing thermal conditions, and maintain service continuity. As inference becomes production infrastructure, static planning and fragmented management tools are no longer sufficient.
This whitepaper explores why DCIM is becoming mission critical in the AI era, examining how real time telemetry, continuous capacity planning, and centralized infrastructure management can help operators improve resilience, optimize efficiency, and support AI inference at scale.
