The Influence of AI on IT Enclosure Design and Configuration
January 17, 2025
Data center growth is on the rise. In the U.S. alone, data center demand is expected to increase by 10% annually through 2030, and the global data center market is projected to be just as bullish during the next decade.
The increase in the number of data centers to process the amount of data generated by artificial intelligence (AI) means the IT landscape is likely to look very different in the short and mid-term future, particularly in the design and configuration of the ideal IT enclosure to handle AI workloads.
AI presents some interesting challenges for the design of IT enclosures in a variety of aspects, most notably:
- The ability to scale server rack space quickly to meet such a rapid increase in processing, particularly as AI data center deployment becomes more variable
- The capacity to house increased server rack density without increasing the physical footprint of an AI data center
The need to simplify and streamline IT enclosure scalability is especially critical for hyperscale data centers. These large IT installations – which can be close to 100,000 square feet in size — are designed specifically for the kind of flexibility and scalability required to process and store high volumes of data.
Because hyperscale data centers are built for adaptability, they are ideal for handling AI’s increased data workloads, and the growth of hyperscale data centers is creating a move for more modular IT enclosures that can be rapidly and easily configured to accommodate increased AI workloads with minimal downtime.
The capacity to house increased server rack densities without increasing the physical footprint of an AI data center also hinges on more modular IT enclosures that are designed for flexibility in high-density applications. This is especially important as the industry definition of high-density continues to shift with the growth of AI computing.
As recently as a few years ago, a 10kW server rack would be considered a high-density application, but technological advancements in computing have made it common to see 100kW of computing power with the same server rack footprint. The growth of AI means data center operators are tasked with increasing server power, computing capacity, and more cooling without significantly increasing the footprint of their IT infrastructure.
There are a host of other ways AI is impacting the design and configuration of IT enclosures. More efficient power distribution and sustainable enclosure cooling are also driving significant evolutions in the right enclosure for AI data centers, and Rittal’s new guide, Understanding the Impact of AI on Data Center Efficiency, outlines these changes and how data center managers can:
- Balance the effective utilization of data center space with the need for high-density racks
- Increase computing capacity without impacting productivity and uptime
- Integrate AI workloads while still prioritizing efficient, sustainable energy usage
As an innovator in the IT space, Rittal can help data center operators establish the kind of nimble, efficient computing framework that can handle the challenges and leverage the opportunities of AI.
