Why AI Data Growth Breaks Traditional Infrastructure Planning

When it comes to AI workloads, compute scales linearly while data scales exponentially, continuously accumulating across training, inference, logs, embeddings, synthetic outputs, and retention windows. Key Takeaways AI data centers now sit inside a resource model that older infrastructure plans were not built to handle. Data center electricity consumption is projected to rise from 485TWh […]