AI Infrastructure: GPU → Network → Data Center
Falling inference costs, surging power demand, cooling technology race — a layer-by-layer dissection of the full AI infrastructure value chain.
The AI infrastructure industry is seeing demand explosions across the full value chain: GPU → networking → power/cooling → software stack. Hyperscaler CapEx has exceeded $300B in 2026, flowing through revenue across the entire chain.
Market Size
Global AI infrastructure investment: $320B+ in 2026 (NVIDIA + Big 3 cloud CapEx combined)
Key Trends
GPU Demand Explosion
Demand for NVIDIA H100/H200/B200 far exceeds supply. GPU consumption surging in both training and inference.
Inference Cost Decline
GPT-4 class inference costs dropped 99% in two years. Cost decline is stimulating demand — Jevons Paradox in action.
Power Demand Explosion
Data center power demand projected to triple by 2030. Cooling technology (liquid, direct liquid) emerging as a new CapEx category.
On-Device AI Growth
AI inference on smartphones and PCs is growing, stimulating demand for edge semiconductors (Qualcomm, Apple).