Compiled by Eamonn Ryan based on the SAIRAC Johannesburg Centre Tech Talk on September 19 by Michael Young, mechanical engineer
Artificial intelligence (AI) is not just a buzzword; it’s deeply integrated into our daily lives and industries, reshaping how we interact with technology. This is Part 2 of a ten-part series.

Michael Young, mechanical engineer. © RACA Journal
From the moment we search for something on Google and receive suggestions—even correcting our spelling—to using apps like ChatGPT for instant information, AI is enhancing our experiences and efficiencies. But how does this relate to the data centre space, particularly regarding cooling systems?
Understanding AI in everyday applications
When we consider AI in applications like YouTube, for example, the platform analyses your viewing habits and serves up recommended videos based on your preferences. Similarly, Google’s search algorithms refine results to meet user intent, even accommodating typographical errors with phrases like “Did you mean this?” These intuitive functionalities illustrate AI’s potential to learn and adapt to user needs, a capability that can be directly applied to managing the operational demands of data centres.
AI has extended its reach into numerous sectors, including:
- Healthcare: AI is revolutionising diagnostics and patient care through predictive analytics and automated systems
- Finance: Institutions use AI to detect fraudulent activities and improve risk management
- Smart cities: AI optimises traffic flows, resource allocation, and urban planning
- Manufacturing: Advanced robotics driven by AI streamline production processes and reduce human intervention
In every instance, the goal is to enhance efficiency, improve decision-making, and minimise costs.
The growing energy demands of AI
However, as AI becomes more pervasive, its energy consumption is projected to increase dramatically. Data centres, which already face significant cooling challenges, must adapt to these heightened demands. Forecasts indicate that the power consumption of data centres could triple in the next five years, largely driven by the increased computational requirements of AI technologies.
This rise in power consumption correlates directly with heat generation. More computing power means more heat—just as your laptop or smartphone overheats during intense use. If data centres cannot effectively manage this heat, they risk shutdowns, affecting reliability and performance.
Cooling solutions: The role of liquid cooling
As power consumption escalates, so do the cooling requirements. Traditional cooling methods may struggle to keep pace, making liquid cooling a compelling option. This system can efficiently dissipate heat, ensuring that critical infrastructure remains operational around the clock.
Liquid cooling solutions, enhanced by AI, can dynamically adjust to real-time conditions, optimising energy use while maintaining ideal operating temperatures. By integrating predictive analytics and machine learning, these systems can anticipate cooling needs based on workload fluctuations, thereby improving overall efficiency.
Conclusion: preparing for the future
As we look to the future, the integration of AI in data centres signifies a shift toward more intelligent, adaptive cooling solutions. Understanding the interplay between increased power consumption and effective heat management is crucial for engineers and cooling specialists. By leveraging AI technologies, we can ensure that data centres remain efficient, sustainable, and reliable in an increasingly data-driven world.