The global shift to AI computing is driving exponential demand for data center capacity. By 2030, global AI data center CapEx is projected to exceed $7 trillion, and power demand will more than double. This proposal outlines a 3–5 year global investment strategy focusing on high-efficiency, AI-optimized data centers and cloud storage infrastructure.
AI training and inference workloads are expanding rapidly, driving both semiconductor growth and infrastructure investment. GPU and accelerator demand is surging, with NVIDIA, AMD, and emerging custom silicon (AWS Graviton, Google TPU) leading the charge.
Chart 1: Projected Global AI Chip Market ($ billions)
Chart 2: Global Data Center Power Demand (GW)
Chart 3: Cooling Technology Adoption (%)
Phase 1 (Years 1–2): Deploy 50–100 MW modular data centers in key low-cost regions (Scandinavia, US Midwest, Singapore). Prioritize renewable grid connectivity and scalable power.
Phase 2 (Years 3–5): Expand to 300+ MW capacity across multiple regions. Optimize utilization (>80%) and secure 10-year colocation and cloud hosting contracts with AI startups, enterprise cloud providers, and sovereign data projects.
Focus: energy efficiency, liquid cooling, hybrid cloud storage, and AI compute hosting. Target 10–12% IRR on facility investment with recurring data storage revenues.
AI data centers are capital-intensive. Typical builds require ~$10–$20M per MW of capacity. With current leasing rates (~$160/kW-month), a 30 MW facility can generate ~$100M annual recurring revenue at 85% utilization.
| Metric | Value |
|---|---|
| CapEx / MW | $12M (AI-optimized) |
| Lease Price | $160 / kW-month |
| Annual Revenue (30 MW) | $100M |
| Operating Margin | 35–40% |
| IRR Target | 10–12% |
Chart 4: Projected Revenue Growth (30 MW Facility, $M)
The AI compute stack is dominated by advanced GPUs and custom ASICs. NVIDIA retains ~93% of AI GPU market share, but hyperscalers’ in-house chips (e.g., AWS Trainium, Google TPU) will gain share through 2030. On the infrastructure side, cooling innovation is critical: immersion and liquid cooling adoption is projected to reach 45% of all new builds by 2030.
AI Infrastructure Ventures is focused on global data hosting and cloud infrastructure investments, combining real-estate and high-performance computing expertise to capture long-term growth in the AI economy.
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