By David Pownall, Vice President, Services, Schneider Electric UK and Ireland
As the world becomes increasingly interconnected, with 40 billion devices projected to be connected to the IoT by 2030, it’s no surprise that data centres are under pressure to meet soaring demand. As artificial intelligence and other energy-intensive technologies grow in popularity, data centre operators will need new and innovative ways to manage the surge in new devices and create resilient infrastructure.
In fact, three-quarters of data centres currently face increased pressure from AI-driven demands, with only three-in-ten decision makers believing that they are doing enough to enhance the energy efficiency of data centres. Creating energy efficient data centres becomes an even more prevalent concern when you consider that global data centre capacity is set to triple in size between 2022 and 2030.
As the data centre industry is catapulted into hypergrowth, operators will need new and innovative ways to manage the surge in new devices, ensuring electrical assets are dependable to minimise unplanned downtime.
Playing it cool
It is imperative that AI data centre growth is decoupled from the environmental impact. For this to be accomplished, low carbon energy sources need to be utilised, new flexible and efficient AI-ready data centre designs must be developed, and sustainable business practices must be put into place. Traditional power and cooling optimisation technologies will need to evolve if they are to support the demands of higher density racks, which accommodate even greater amounts of computing power.
Technologies such as liquid cooling, software-based cooling optimisation, and advanced airflow management are becoming increasingly popular, making it possible to maintain optimal temperatures whilst consuming less energy. With proper airflow management, operators can ensure that cool air is distributed evenly throughout the data centre, preventing hot spots and improving overall cooling efficiency.
AI’s role in predictive monitoring and maintenance
Though artificial intelligence is creating increased demand for data centre infrastructure, it could also hold the key to unlocking energy efficiency gains when it is integrated into data centre infrastructure management (DCIM) software.
When AI is integrated within an infrastructure management system, it collects and analyses data from thousands of sensors, monitoring variables such as temperature, humidity, server loads, airflow, and energy consumption. AI can also learn from external data sources, such as weather data. Instead of controlling cooling based on a fixed schedule, AI aggregates past data and predicted future insights to make adjustments in real time.
This is a gamechanger for data centre operators looking to optimise their resources and prevent existing parts from overheating if a sudden shift in weather, such as a heatwave, occurs. With tools that track energy usage, temperature, and performance metrics around the clock, operators can confidently allocate resources, as well as identify potential areas to optimise energy use.
AI & automation
Along with anticipating shifts in temperature, AI algorithms can forecast hardware failures and schedule maintenance before issues snowball, reducing downtime and waste resulting from burnt out parts. By switching to a more proactive approach, operators can keep equipment performant for longer periods of time, prolonging its lifespan and dependability. Proactive asset management is already proving its worth, with some sites reporting reductions in critical asset failure by up to 60%, with maintenance visits only required every five years instead of every three.
AI technologies are also making a significant difference for data centre operators by automating tedious manual tasks, including backup management, load balancing and system updates. Delegating these tasks to AI not only reduces the margin for human error: it also enables operators to focus their energy on more strategic activities which require a more discerning human eye.
AI is also advancing data centre security through tools such as remote management. By deploying cloud-based AI tools, operators can gain visibility across several sites at once: an especially valuable tool for teams working across hybrid environments. These tools offer operators automated alerting should performance deviate from an agreed baseline. Automated alerting not only reduces the likelihood of human error; it also acts as the ‘eyes and ears’ for data centre operators at any time of day, anywhere. Operators are informed at speed should potential security or equipment issues arise, so system vulnerabilities can be addressed in good time, before they impact end-users and services.
Into the future, AI integrations in infrastructure management will play a vital role in facilitating resilient, future-ready data centres that the world can depend on. Tools such as remote monitoring, cooling, and predictive maintenance will all play a vital role in ensuring the longevity and resiliency of these structures as demand grows over the next decade.
This article appeared in the July/August 2025 issue of Energy Manager magazine. Subscribe here.