Data centres are now the hubs of our digital world, managing, processing and storing data, and supporting anything from global cloud computing operations to enterprise applications.
In just a few years, the global community has rapidly transitioned towards more data-driven decision-making and automation – and in doing so, it has increased its reliance on technology.
Data centres have powered our demand for these advanced computing capabilities, while helping to facilitate the rapid expansion of artificial intelligence (AI) technologies.
However, the speed of AI adoption has threatened to overwhelm the data centre infrastructure that supports it and the industry is now scrambling to keep up with the demands that are being placed upon it.
The issue is multi-faceted.
AI has substantial computational requirements, and its high levels of processing power have increased data centre energy consumption and the thermal output within racks. Meanwhile, real-time data processing is increasing pressure on existing storage systems and network bandwidths.
The AI revolution has also appeared at a time when the IT sector is seeing a massive expansion in cloud-based software solutions and the widespread adoption of smart devices, cryptocurrencies, the Internet of Things (IoT) and machine learning.
To create the capacity needed to accommodate all these developments, data centres are trying to rapidly scale-up their infrastructure by expanding the available white space, improving cooling systems and optimising resources. But the rate of industry change and the necessary degrees of transformation have created a demand shock across the supply chain, and this is leading to major bottlenecks while fuelling cost inflation.
Clearly, structural changes on this scale are difficult navigate and hard to sustain, particularly when the market is so volatile and innovations (such as the Deepseek AI model) are being brought to market very quickly making future predictions near impossible.
However, there are also ways that colo and enterprise operators (with fewer financial resources) can quickly adapt to create competitive advantage and protect themselves from short-term pressures.
Building in resilience and scalability, for example, means that data centres can create flexible, agile spaces that can rapidly change as the industry adjusts to the demands of the new technology. In turn, this should help buffer owners and operators from substantial future capex outlays, while maximising returns on investment.
In Rittal’s Data Centre ebook, we consider all these issues in more detail.
We consider what practical steps data centre operators can put in place to future-proof their new and upgraded facilities within such unpredictable operating environments, to meet the challenges of rapidly evolving AI technology.
We also look at how to minimise cost pressures and any disruption to data centre day-to-day operations during infrastructure upgrades, and how manufacturers within the supply chain, from chips to cooling infrastructure, are rapidly innovating to ensure that future AI workloads can be supported. Download your copy today.