Choosing the right home for AI infrastructure Read here
As AI workloads grow in scale and power density, organizations face a critical infrastructure decision. Should existing facilities be retrofitted, new data centers built, or workloads deployed through colocation and cloud providers? Each option carries different implications for cost, speed, scalability, and operational control.
This Schneider Electric whitepaper presents a practical decision making framework for evaluating these options. It explores the tradeoffs between retrofit, build, and outsource strategies while outlining a five step assessment to determine whether existing sites can realistically support AI infrastructure and long term capacity growth.
Inside you will learn:
How to evaluate retrofit, build, and outsource strategies for AI workload deployment
The role of time to market, scalability, and operational capability in infrastructure decisions
How total cost of ownership and data sovereignty influence deployment models
A five step process for assessing whether existing facilities can support AI ready infrastructure
Read here
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