As of 2024, New York City was home to 40,000 AI professionals, 2,000 AI startups, 35 AI “unicorns”(startups with valuations in excess of $1 billion). And for every fresh-faced AI startup, there are likely a dozen or more established enterprises wading into the space with AI initiatives of their own. So, it’s safe to say that the AI boom is well underway in New York City.
At the same time, however, the industry isn’t without its headwinds; and for young startups and established enterprises alike, infrastructure is a source of many of those challenges. The uniquely resource-intensive nature of AI development—with its massive data demands and extensive computing requirements—makes infrastructure uniquely complex and costly.
However, while most business decision-makers think in terms of the “cloud vs. on-premises” dichotomy, there is actually a third option — colocation data centers. And for many organizations, it’s the ideal solution for handling their growing AI workloads.
Costly, Time-Consuming, and Restrictive: The Pain of AI Infrastructure Development
As cloud costs soar and the data and compute demands of frontier models continue to grow, many businesses are considering developing their own on-prem or dedicated data center environments for handling AI workloads.
While long-term operational expenses are significantly lower than cloud-based solutions, this approach is anything but cheap. Upfront capital requirements can often be prohibitively expensive, especially for early-stage startups. And expenses are far from the only problem. Designing and deploying on-prem environments for AI workloads is complex and time-consuming, taking anywhere from 9 to 12 months on average. In today’s fast-paced, hyper-competitive AI landscape, that’s practically a lifetime, slowing your time to market and inviting competitors to capture market share while you toil over infrastructure concerns. And to top it all off, it’s all but inevitable that you’ll hit dead ends down the road as you attempt to scale beyond the limits of your facilities.
Interconnected Colocation Offers NYC’s AI Businesses the Best of All Worlds
Thankfully, there’s a solution. Colocation data centers, or colocation facilities, allow businesses to run AI workloads that they don’t want to place in the cloud, but also don’t want to operate in a self-managed, on-premises environment. These shared data center facilities—where businesses rent space to house their servers, storage devices, and networking equipment—provide essential infrastructure services such as power, cooling, physical security, and high-speed network connectivity; enabling companies to avoid the costs and complexities of building and maintaining their own environments.
As a result of this unique arrangement, colocation centers allow businesses to launch quickly, expand freely, and manage costs effectively — making it an ideal solution for growing startups working with resource-intensive AI workloads.
- Scalability – One of the main benefits of a colocation data center is that it provides the infrastructure and capacity needed for your AI workloads to grow indefinitely. While on-prem deployments are limited by the physical and operational limitations of one’s facility, in a colocation facility, the amount of resources available to host your infrastructure is virtually limitless.
- Cost-Effectiveness – In addition to dramatically reducing one’s initial capital expenditures, colocation facilities provide some unexpected operational cost savings as well — especially around things like electricity, cooling and physical security, which will be less costly in a dedicated colocation facility specifically designed to provide these resources at scale.
- Reliability – Colocation data centers are designed to host infrastructure. And they do so using the most reliable and performant Things like backup power supplies, cutting-edge cooling systems, and top-of-the-line security all ensure your AI workloads remain safe and stable. Meeting the same standards of reliability in an environment of your own, without the benefit of economies of scale, is often too costly to even consider.
- Speed – With colocation facilities, organizations are able to reduce and manage long-term costs, without sacrificing the speed and agility needed to get your AI innovation to market fast. In such a competitive, fast-paced industry as AI, being able to get your innovations up and running quickly is absolutely essential for success.
For All But a Few AI Businesses, Colocation Just Makes Sense
Unless you anticipate running very small workloads with zero intention of scaling, colocation is almost certainly a more cost-effective and reliable solution than developing one’s own data center environment. Because of AI’s uniquely intense infrastructure demands, the odds of this being the case for most AI businesses is quite small.
Colocation providers can host your AI infrastructure more reliably, and cost-effectively than you can host it yourself. Plus, they may also offer managed services, making your AI company even faster, more agile, and free from infrastructure concerns, so your team can focus on innovating and leading in this ever-evolving industry of AI.
