Infrastructure Matters: How AI-Ready Data Centers Can Kickstart Innovation

Data is the fuel for AI, and your AI success depends on it. For years, enterprises have faced growing volumes of data and increasing data complexity. While nearly every business is eager to get up to speed with AI, many feel they’re not ready to capture AI’s potential.[1] Infrastructure is a big piece of that puzzle, since AI requires the most reliable, secure, interconnected, high-performance infrastructure on the market.

The best way for enterprises to effectively leverage all their data for AI is to employ state-of-the-art, high-performance infrastructure that can meet their needs both now and in the future. This typically requires different types of data centers, depending on the phase of the AI workflow. And they should all be interconnected for seamless data transfer at speed.

Hyperscale data centers are the best choice for service providers training their own large language models since they offer massive computational power and storage capacity for large datasets. Colocation data centers are perfect for enterprise workloads that require midsize capacity, like training private AI models and doing model tuning. Colocation facilities can uniquely address data privacy and sovereignty for proprietary datasets while providing interconnection to AI ecosystems. Edge data centers are the best option for retrieval augmented generation (RAG) and inference workloads since you can choose the locations closest to your user communities. Most enterprises will need a mix of these solutions, all working together to achieve their AI goals. In addition, AI-ready infrastructure requires access to reliable, efficient power, advanced cooling techniques and secure connectivity across the AI deployment.

To continue the conversation around AI-ready infrastructure, we asked four industry experts to share their thoughts on the role of AI-ready data centers in the future of AI. Here’s what they had to say:

Choose the right data centers, and don’t forget power and cooling

“We know AI isn’t just one process happening in one place. It’s a series of interconnected processes occurring all around the world. Therefore, in addition to needing access to efficient power and advanced cooling, you also need an interconnected platform of AI-ready data centers to meet the needs of all of your AI workloads.”

— Tiffany Osias, Vice President Colocation Services, Equinix

Hear more from Tiffany in this video:

A robust and well-planned infrastructure is essential for AI readiness

“Infrastructure plays a crucial role in enabling enterprises to be AI-ready by providing the necessary foundation for performance, scalability, and security. The challenge is that traditional data centers are not equipped to manage the requirements of AI. This includes using high performance architecture to manage data demands, meeting power and cooling requirements, and having access to proven facilities infrastructure that allow them to move quickly. A robust and well-planned infrastructure is essential for AI readiness and having the right infrastructure allows companies to manage their resources and capabilities without limitations.”

— Chris Campbell, Senior Director – AI Solutions, World Wide Technology

Preparing for AI means rethinking your digital infrastructure

“To prepare for AI’s impact on digital business, organizations must rethink their digital infrastructure to support next-generation data-intensive applications. AI-ready datacenters are essential, as traditional designs lack the capacity to handle the power-intensive needs of GPU accelerators and advanced CPUs. Flexibility in deploying hybrid, multicloud, and edge architectures is also critical, emphasizing high-bandwidth, low-latency interconnections to support distributed applications and users effectively.”​

— Dave McCarthy, VP, Cloud and Edge Infrastructure Services, IDC

Supercomputing is accelerating the shift to an AI-first world

“Our supercomputing cluster is more than infrastructure — it’s a catalyst for accelerating the shift to an AI-first world. By taking full control of our computing power, we can innovate faster, optimise resources, and push the boundaries of AI’s potential. This investment isn’t just about solving today’s challenges; it’s about driving tomorrow’s breakthroughs. We’ve built a scalable, flexible, and solid foundation to lead in a rapidly evolving landscape.”

— Karim Beguir, Co-Founder and CEO, InstaDeep

Design an infrastructure that will be a foundation for innovation

AI success requires enterprises to design scalable, resilient, flexible IT infrastructure that can tackle the hefty performance requirements of AI. No doubt, AI requirements will continue to evolve, so why not build an AI foundation that’s future-proof with AI-ready data centers?

For more insights on how to future-proof your AI-driven data strategy, read the Equinix Indicator.

[1] Mike Moore, Companies are feeling the urge to get up to speed with AI – but many simply aren’t ready, Tech Radar, November 25, 2024.