AI is reshaping data center infrastructure across Asia. This transformation goes beyond simply increasing density. The real disruption comes from how AI workloads behave. Large-scale GPU training and inference create spiky, bursty utilization patterns, where thousands of GPUs synchronize and ramp within seconds. These events can push utilization well beyond nominal levels, generating sudden power surges and localized thermal spikes that traditional designs were never built to absorb.
The impact cascades quickly. On the power side, unmitigated AI workload spikes can drive transient loads upstream, contributing to voltage instability and excessive battery cycling. Rack-level mitigation reduces infrastructure oversizing requirements by 50% or more, according to this Vertiv paper.
If you operate in Asia, your data center faces unique challenges from grid constraints, warm climates, and rapid AI adoption. Your infrastructure needs to go beyond average load calculations. The white paper 'AI Workload Management: Designing Efficient Cooling and Power Architectures' examines volatility management in modern data centers. You'll learn how rack-level power buffering, advanced UPS architectures, and liquid cooling systems with CDU buffering work together. These solutions help stabilize both electrical and thermal behavior.
Download the white paper to explore a real-world AI workload scenario and see how integrated power and cooling strategies can reduce peak demand, limit thermal shock, and support scalable AI growth across data centers in the region.
