Artificial intelligence (AI) has been catapulted into the mainstream, with AI models no longer working in the background and now taking centre stage. Almost every industry is looking for new AI functionality to streamline processes and improve results. In this new digital landscape, data centres are uniquely positioned to provide and benefit from AI applications.
Training and delivering AI requires enormous amounts of computing power and data storage. Both future and traditional data centres will provide these functionalities as the backbone of a tech-driven world. However, this increased demand also requires that data centres use new technologies such as AI systems to provide a more effective, secure, and efficient service.
In this blog, we explore how AI is shaping the future of the data centre industry. We’ll discuss how current and future data centre AI and automation are changing operations, improving security, and enhancing resource management.
Tipping point
AI has reached a tipping point into widespread adoption, creating massive demand for data centre capacity. It is not just a case of ‘build more racks’ as the requirement differs from what has come before.
Firstly, this is something different to cloud adoption. Cloud computing has been described as simply moving workloads from one network infrastructure to another – while digitisation and cloud deployment have resulted in vastly increased traffic, it was fundamentally a shift in infrastructure.
However, AI is something completely new – extensive large language model (LLM) processing requirements, for example, did not exist before. It would be a mistake for the industry to look at AI as a natural continuation of cloud adoption – and capacity must be planned with this in mind.
There is another way in which AI shifts the calculation. While LLM requires hefty processing power, there is no real latency sensitivity. Users do not care how long it takes for results to be generated. This is very different to IoT or 5G data requirements. The implication is that facilities built primarily to respond to certain types of AI are less location-dependent than in the past.
Future of data centres
While AI has already significantly impacted our world, it’s important to remember that innovation is speeding up. Future data centres must evolve along with tech to provide an efficient and effective service.
We may see advanced AI, quantum computing, and other emerging technologies shape the next generation of data centres. These cutting-edge technologies promise to deliver greater efficiency and advanced features.
As AI becomes a fundamental part of data centre operations, issues of transparency and accountability will become paramount. Sustainability will also play a huge role in data centre AI decisions. Resource-hungry workloads use advanced CPUs and GPUs that require advanced liquid cooling systems to protect against hardware damage. According to IBM, data centre energy consumption is expected to increase by 12% in the next six years.
Using AI will ensure data centre providers evolve with these changing demands, providing the hyper-scale digital backbone of the future in a considered, ethical way.
Impact on data centre operations
Fundamentally, AI and machine learning algorithms are extremely good at spotting patterns in datasets. They then apply their learning to future tasks by automating and streamlining daily operations.
Data centre operators have embraced AI to help streamline the daily running of services. In a 2022 survey by Uptime Institute, almost 60% of data centre owners said they trust an AI model to make operational decisions.
Operators can use predictive analytics to improve data centre cooling systems in real time. Delivering the power and storage required by modern computing demands produces incredible heat. By using AI to cool hardware more efficiently, providers can cut costs and improve energy efficiency.
AI can also help reduce IT infrastructure inefficiencies. Predictive analytics can help providers fine-tune power allocation and rack space, resulting in lower operational costs, improved power usage effectiveness (PUE), and better data-driven decisions.
Optimising resource management
Modern companies are running demanding workloads on data centre infrastructure. This means data centre operators must provide the power, storage, and connectivity demanded by new and current tech and become more efficient.
Some data centres already use AI to improve workload management and allocation. These solutions can help use hardware and network services more efficiently, avoid downtime, and provide a consistently high level of service.
Predictive maintenance helps ensure business continuity. AI algorithms can spot issues before they happen, drastically reducing downtime and hardware replacement costs.
AI in data centres
AI is reshaping the data centre industry. Predictive analytics are helping to automate routine operations and streamline resource management while improving defences against emerging security threats.
AI’s role also extends to managing resources. Predictive maintenance and dynamic workload management bring significant cost savings, improved delivery, and protection against service outages.
Emerging technologies will further shape the use of AI in data centres. By combining ethical initiatives with new AI technology, data centres can provide the high-performance cloud services required by future businesses.
