Digital Twins Bring Down the Degrees

Artificial intelligence (AI) workloads continue to surge as humans find new ways to spin the technology’s capabilities, transforming the world as we know it. From troubleshooting device issues and minimizing the risk of cyberattacks to content creation and detecting underlying health issues, there is no bar too high for AI.

Yet as AI advances, it brings a new challenge: data centers must cope with a sixfold increase in demand, with racks running workloads exceeding 100kW becoming commonplace. This leads to data centers producing thermal loads that traditional air-cooling systems were not designed to keep up with.

Direct-to-chip liquid cooling is quickly moving from niche applications to becoming the mainstream solution for responsibly sustaining these workloads. Now, thanks to digital twins and their ability to simulate the behaviour of these systems, data centers can understand how liquid cooling and other systems will run in physical facilities before they implement them. That’s why 58% of organisations already use them to plan, monitor, and run AI.

Facilitating the Big Shift

As reliance on AI intensifies, data centers are under pressure to deliver peak performance while managing unprecedented thermal loads. Traditional air-cooling systems are struggling to keep up. In response, some facilities are turning to liquid cooling, which absorbs and transfers heat far more efficiently thanks to the superior thermal conductivity of liquids compared to air. This technology is especially well-suited to dense, high-performance environments, and can be deployed in smaller spaces where legacy systems fall short.

Without the shift to liquid cooling, facilities risk costly errors, system outages, and in some cases, complete shutdowns. This is because prolonged exposure to high temperatures can degrade hardware and overwhelm air cooling infrastructure. Despite its advantages, just over a quarter of decision-makers (26%) say they would never consider liquid cooling, highlighting a critical gap in awareness as AI-driven infrastructure demands continue to grow.

Implementing a new cooling system is no mean feat, which is why 41% of all decision-makers feel nervous about introducing liquid cooling in their organization’s data centers. Cost is one such obstacle that could contribute to this nervousness, particularly for existing facilities that lack the infrastructure to support liquid cooling. What’s more, retrofitting is not only costly, but because air-cooling systems can require extensive redesign, there is a risk to any existing loads. On top of that, adopting liquid cooling requires a new skill set for those facilities that do not already run some liquid-cooled loads, from managing fluid dynamics and preventing leaks to handling specialized maintenance routines.

Reluctance to Embrace

Beyond cost and skill challenges, reluctance to adopt liquid cooling often stems from infrastructure and integration concerns. The concept itself can feel more intimidating than traditional air-based systems, which are familiar, standardized, and relatively plug-and-play. In contrast, liquid cooling requires the coordination of multiple components, pumps, manifolds, and heat exchangers from various suppliers. This introduces complexity, compatibility issues, and operational risk. For many facilities, the idea of overhauling their cooling infrastructure feels far more disruptive than deploying an entirely new data center with liquid cooling built in from the start.

Moreover, although many new data centers are being designed with liquid cooling in mind, there are still few long-term, real-world examples where the technology has been thoroughly stress-tested and proven. This lack of operational history leads to ongoing doubts about its reliability and ease of maintenance. Consequently, unless innovation is a central focus of a project, many operators prefer to stick with tried-and-tested air-cooling solutions until they can observe the outcomes of other facilities’ experimentation.

The Future of Smarter Infrastructure

Despite the many challenges surrounding the implementation of liquid cooling, such as cost, complexity, and the need for specialized skills, digital twins have emerged as the essential solution to overcome barriers. By creating detailed simulations of liquid cooling systems before they are physically deployed, digital twins allow operators and designers to explore critical factors like coolant flow and distribution, resilience to failure, and coexisting air-side cooling. This early-stage insight not only boosts confidence but also helps future-proof facilities by identifying potential issues and optimizing designs well in advance.

As a result, digital twins significantly reduce the risks associated with liquid cooling adoption, cutting down on unnecessary costs due to errors, delays, and the steep learning curve traditionally involved. They provide a clear, interactive blueprint that guides decision-makers through every step of implementation, making the transition smoother and more predictable.

What’s more, while digital twins are transforming cooling strategies, their impact extends far beyond. They can be applied across the entire data center ecosystem, helping to identify stranded capacity, optimize workload distribution, and enhance overall operational efficiency.

Designing Tomorrow’s Demands

Digital twins are the North Star, guiding data centers toward future-proof operations, seamless liquid cooling integration, and more. They empower decision-makers to scale responsibly and meet rising demand. Now, as AI workloads continue to push data centers beyond the limits of legacy systems, digital twins are fast becoming the indispensable tool for smarter, safer, and more scalable infrastructure management.