As AI continues to be a fundamental driver of digital transformation, one challenge stands clear for hyperscalers: how do you build the infrastructure that can manage high-density workloads, process endless amounts of data and do it all sustainably?

Hyperscalers are no strangers to these issues. They’re grappling with the need for higher-density compute environments to support AI workloads, the urgency to reduce energy consumption without sacrificing performance and the ever-increasing demand for sustainability. And if that wasn’t enough, there’s the rapid evolution of GPU technology—which is now pushing cooling solutions to their limits.

The Need for High-Performance, Sustainable AI Infrastructure

To support AI and high-performance computing (HPC) workloads, data centres need to evolve. It’s no longer just about providing space, it’s about developing the right environment that can meet the growing demand for computational power without compromising efficiency or sustainability.

A good example of this is our Harlow campus. Designed specifically with AI in mind, we are currently building out our third data centre, KLON-03, which will provide 17.6MW of liquid-cooled infrastructure and hybrid cooling solutions. This facility will be first of its kind in the UK, allowing us to support high-density, bespoke GPU environments, giving our clients the scalability and flexibility they need to stay ahead of the curve in critical AI infrastructure.

Ultimately, supporting intensive AI workloads requires sophisticated data centres specifically engineered with flexible hybrid cooling solutions. Data centre operators that proactively incorporate these technologies can significantly future-proof their facilities.

Sustainability as a Core Principle

With so much focus around meeting sustainability goals without sacrificing the performance AI workloads demand, a data centre needs to be built for the long-term. 

When we expanded the Harlow site, it was fundamental we had 100% renewable energy and integrated HVO in backup generators, reducing carbon emissions by 90% compared to traditional systems. We’re also one of the few operators in the UK currently exploring private-wire solutions to nearby solar arrays, and those under development, so we can best utilise renewable power, without having to rely on the grid.

Internally, we also embrace hybrid cooling technologies, which combine liquid and air cooling. These solutions not only maximise energy efficiency but also enable us to meet rising AI demands while keeping energy consumption under control. We’re also switching some of engineering solutions to a more modular approach so we can be agile with our infrastructure as the requirements from our customers flex.

Partnerships for Innovation

The rapidly advancing field of AI requires collaboration with key industry partners. No one company has all the answers, which is why partnerships are so important. For us, working with NVIDIA, Arm and NSCALE and others, mean we stay on the cutting edge of AI innovation and provide access to the latest technologies in GPU performance and cooling solutions. The ability to dynamically respond to these rapid technological advancements will prove crucial in supporting the relentless pace of AI innovation.

These partnerships enable us to continuously adapt our infrastructure to meet the needs of the future, ensuring that we’re not just keeping up with AI demands but actively shaping the future of AI infrastructure.

Looking Ahead: The Future of AI-Ready Infrastructure

By continuously adapting to evolving AI-driven demands, it is possible to sustain high standards of sustainability, energy efficiency and operational reliability. The future is about staying ahead of these challenges and ensuring that the infrastructure we build today is ready for the AI workloads of tomorrow.

Understanding the complexities of AI-ready infrastructure and a focus on providing flexible, high-performance and sustainable solutions will help cloud providers and hyperscalers grow capacity with confidence and continue to lead the way in AI innovation.