Singapore Data Centres Face Cooling Challenge as AI Demand Grows
Source: Singapore Business Review
Singapore data centre operators are under pressure to improve cooling efficiency as AI, cloud, and HPC workloads push power demand higher, with humidity and limited natural cooling making tropical facilities harder to optimise at scale.
Singapore's data centre operators face mounting pressure to improve cooling efficiency as artificial intelligence, cloud computing, and high-performance workloads drive up power demand in one of the world's most land- and energy-constrained markets.
Jon Curry, Vice President Operations for Asia-Pacific at Digital Realty, said the challenge is not simply keeping facilities cool but doing so efficiently as computing demand rises. Singapore's year-round heat and humidity give operators fewer opportunities to rely on natural cooling compared to temperate markets like Korea or Japan. Dr Tan Hong Ming, Senior Lecturer at NUS Business School, noted that humidity is often overlooked in data centre cooling, adding energy demand and operational complexity.
Talent is another constraint. Tan said operators need people who can run digital twins, machine learning temperature models, and AI tools to support both modelling and operations. Curry added that solutions vary by facility, with some sites needing operational changes and airflow management while others may require liquid or hybrid cooling. Digital Realty has tested AI tools in Singapore and Melbourne that assist operators in making real-time cooling adjustments during workload spikes.
The stakes go beyond operational efficiency. Tan said better cooling can free up electricity for other parts of Singapore's economy, including housing, transport, manufacturing, and digital services. Older facilities may lack sufficient sensor coverage and environmental telemetry to optimise confidently, and the surrounding microclimate also affects how hard cooling systems must work.
Why it matters for Singapore: The data centre cooling challenge is a microcosm of Singapore's broader AI growth dilemma: how to support rapidly expanding computing demand within tight energy and land constraints. With AI workloads projected to multiply in the coming years, the city-state's ability to cool infrastructure efficiently will directly affect its competitiveness as a regional AI hub. Solutions developed here, from liquid cooling to AI-managed climate systems, could become exportable expertise for other tropical markets facing the same constraints.