Why data centre cooling is becoming a channel decision in AI infrastructure

Much of the conversation around AI infrastructure has focused on chips, power availability, and new data centre construction. Those are real constraints, but they’re not the only factors shaping how quickly new capacity comes online.

Recent announcements from NVIDIA around rapid AI infrastructure expansion reinforce just how quickly this market is moving. But while compute is evolving on an accelerated timeline, the rest of the infrastructure stack, including data centre cooling, isn’t moving at the same pace.

Across the industry, there’s a growing gap between what gets planned and what actually gets deployed. Infrastructure designs may look viable on paper, but turning those plans into live, revenue-generating environments is taking longer than expected. Labor shortages, supply chain delays, and integration complexity are all contributing to that slowdown.

This is where data centre cooling is starting to have a much more direct impact. Cooling is no longer just a supporting system inside the facility. It’s increasingly influencing when infrastructure is ready to go live.

For many operators, the issue isn’t identifying a cooling solution. It’s implementing it within the timelines that modern AI infrastructure demands.

Data centre cooling is moving into the channel

This shift is happening alongside a broader change in how infrastructure is delivered.

Compute, networking, and cloud solutions already move through MSPs, system integrators, and technology advisors. These partners help customers design, procure, and deploy complete environments, and that model continues to expand.

The numbers reflect that momentum. The technology services distribution (TSD) market reached $16.6 billion in gross billings in 2024, growing 14.5% year over year. The top six providers now control more than 70% of the market, all while continuing to deliver double-digit growth. That level of consolidation highlights how central partner ecosystems have become to infrastructure delivery.

Data centre cooling is beginning to follow that same path. When cooling is introduced earlier, alongside compute and power, projects tend to stay on track. Integration is more straightforward, and deployment timelines are easier to manage. When it is introduced too late, it often creates delays or forces redesigns that slow progress.

For MSPs and channel partners, this represents a shift in responsibility. Cooling is no longer a downstream consideration. It is becoming part of the overall infrastructure strategy, shaping how solutions are designed and delivered from the start.

Deployment speed and simplicity are now driving cooling decisions

The data centre industry has always prioritised reliability, and for good reason. Operators are responsible for uptime, so decisions are typically grounded in what’s proven and predictable.

At the same time, AI is accelerating the pace of infrastructure demand. Customers are pushing for faster deployment timelines, often in environments that were not originally designed for high-density workloads. This creates a balancing act between speed and stability.

That gap is becoming more visible as new AI architectures are introduced at a faster cadence. NVIDIA, for example, continues to push the pace, but operators aren’t rebuilding their data centres every year. That creates a mismatch where cooling infrastructure needs to support what’s coming next, while still working within the constraints of what’s already deployed.

Data centre cooling sits directly in the middle of that dynamic. Solutions that require major facility changes or introduce operational complexity can slow adoption. Solutions that are modular and easier to integrate can help move projects forward without adding risk. That’s why the criteria for evaluating cooling is changing.

It’s no longer just about performance. It’s about how easily a solution can be deployed within real-world constraints. That includes lead times, integration requirements, scalability, and day-to-day operation. It's a question of “what can we deploy now that will still hold up as requirements change.”

This is where modular approaches are gaining traction. For example, rear-door heat exchanger systems using two-phase refrigerants remove heat directly at the rack level, without introducing chilled water into the data hall. These systems can support a wide range of densities, including AI workloads, while allowing operators to scale incrementally.

Because they are designed to fit within existing environments, they can be deployed more quickly and with less disruption, which is increasingly what customers are asking for.

Data centre cooling is becoming part of the infrastructure strategy

As AI adoption expands beyond hyperscale environments, more enterprises and regional providers are looking to support higher-density workloads. Many of these organisations rely on MSPs and channel partners to guide infrastructure decisions, especially when it comes to integrating new technologies into existing environments.

Aligning data centre cooling with the channel makes advanced infrastructure more accessible. It allows partners to deliver solutions that account for compute, power, and cooling from the outset, rather than addressing them separately. It also helps close the gap between planning and execution.

Cooling has always been essential to data centre operations, but its role is evolving. It’s no longer just a facility-level decision made late in the process. It’s becoming a core part of how infrastructure is planned, delivered, and scaled.

For MSPs, this creates a clear opportunity. As cooling becomes more closely tied to deployment timelines and overall infrastructure performance, it becomes a more strategic part of the conversation. Because in this next phase of growth, success isn’t just about what gets built. It’s about how quickly it can be delivered and put to work.