Powering up: Preparing your data center for AI workloads

As businesses increasingly embrace AI solutions, the demand for hardware capable of handling AI workloads grows. Whether upgrading existing infrastructure or building from scratch, organizations face critical decisions — and the explosion of generative AI (GenAI) and large language models (LLMs) like ChatGPT adds urgency to this challenge. While the costs of AI infrastructure are substantial, businesses must weigh the options: upgrade existing hardware, optimize it for AI or invest in new systems. In this evolving landscape, the demand for AI-ready data centers has surged, requiring reliable infrastructure with higher computing power and energy efficiency.

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Preparing a data center to handle AI workloads requires a comprehensive approach to infrastructure design, energy management and space utilization. This report will explore the critical steps that facilities infrastructure leaders must take to ensure their data centers are optimized for AI. From assessing power requirements and prioritizing advanced cooling solutions to designing efficient layouts and implementing sustainable practices, here is a roadmap for transforming your traditional data centers into AI-ready powerhouses — figuratively, of course.

Topics include:

Power requirements
Cooling solutions
Cabling and pathways
Space and physical footprint utilization
Sustainability and energy management

Each section will cover why these topic areas should be prioritized, the risks of not doing so and steps for putting each item into action.