AI Stress Test Report
Can data centers keep pace with AI?
AI is accelerating fast — but can data centers keep pace?
As organizations scale AI from model training to real-time inference, the demands on data centers are growing. Higher power density, more complex network traffic and tighter performance requirements are influencing how facilities are designed, built and connected.
Yet the challenge is not simply one of capacity. It is also a question of coordinating compute, networks, power systems and deployment timelines.
We commissioned a comprehensive study that models three potential growth trajectories: accelerated, steady and slower AI adoption, then stress test each scenario against real-world constraints. By examining how demand interacts with power availability, land use, supply chains and capital investment, the report provides a clearer view of where pressure points are most likely to emerge — and how the industry can prepare for them.
The result is a forward-looking perspective on how global data center infrastructure must evolve to support AI sustainably, efficiently and at scale.
What you’ll learn
This report explores how AI is transforming the global data center landscape, what this means for the future of the industry and how operators and policymakers can respond.
How AI is changing infrastructure requirements
From network traffic to high-density GPU clusters, AI is redefining performance expectations in compute, networking and facility design.
Where the real constrains are emerging
Power availability and deployment timelines — not fiber capacity — are increasingly the gating factors in scaling infrastructure.
What different growth scenarios could look like
The study models accelerated, steady and slower AI-adoption pathways and their implications for energy demand, land use, capital investment1 and supply chains.
How operators and policymakers can stay ahead
New approaches to planning, design and coordination will be critical to avoiding bottlenecks and enabling sustainable growth.
Data center case studies
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