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The limited capacity in the data center sector is likely to push the local data center industry toward higher-value AI use cases.
Kiran Karunakaran, partner at Bain & Company, expects the city-state to take the lead in the region to convert existing data center capacity to AI-enabled facilities.
He estimates that firms operating large-scale cloud platforms, such as Google and Amazon, account for 70% of data center usage in the country. These companies will likely leverage their presence in Singapore for AI workloads while shifting more traditional workloads to Malaysia and Indonesia.
“Many of the data centers in Singapore have already started thinking about AI workloads, says Karunakaran. He adds that in terms of readiness, they are “already ahead” when it comes to availability of graphics processing units – semiconductor chips used to train and run AI models – as well as conversion of existing Tier 4 data centers to AI-enabled ones.
Even with Singapore’s move to increase allocated capacity to the industry, the sector still faces energy and water constraints. In May, Singapore said that it will provide at least 300 megawatts (MW) of additional capacity for data centers in the near term.
Janil Puthucheary, the country’s senior minister of state for communications and information, said in a speech in May that another 200 MW or more could be made available to operators who tap green energy.
Singapore currently has more than 70 data centers, which have a total of 1.4 gigawatts of capacity.
Even with the expected shift toward AI-enabled facilities, Niccolo Lombatti, media and telecoms analyst at BMI technology, says that the types of AI workloads executed in Singapore also matters.
Currently, there is a lot of focus on training and improving AI models, such as OpenAI’s ChatGPT and AI Singapore’s Sea-Lion large language model. But Lombatti says that the nation will not have sufficient capacity to train such models, noting that the average data center development in the US already takes up 200 MW.
“I think that the 300 MW may be better used – and I think that will be the plan – in AI inference, which requires less power density but requires being much closer to the user,” he adds.
AI inference refers to the process in which AI models generate their own results after being trained on data sets. For instance, AI inference for autonomous driving could be done locally in Singapore for optimal performance and safety.
Another factor supporting the growth of AI in the country is its connectivity, according to Serene Nah, managing director and head of Asia Pacific at Digital Realty. She believes that Singapore can retain critical workloads, and remain a key connectivity hub in the region by providing a range of connectivity options.
“Singapore’s world-class connectivity makes it a prime location for deploying cutting-edge AI. Co-locating AI with global networks in Singapore allows for seamless data processing across vast distances and access to a wide range of customers,” Nah explains.
She adds that there are several ongoing initiatives to import renewable energy and develop low-carbon energy technologies locally.
Local readiness for AI
Singapore’s data center industry is taking on the challenge of hosting these AI workloads.
Bill Chang, CEO of Singtel’s data center arm Nxera, says that the telco is phasing out its older, less efficient data centers and building more sustainable facilities in their place.
“This involves building highly efficient data centers that optimize land, power, and water use through advanced technologies, such as liquid cooling and smart operations, to achieve better overall energy efficiency and operational resiliency, and making a complete switch to renewable energy from the grid for our internal operations and common utilities,” he explains.
Singtel’s 58 MW Tuas project will double the company’s operational capacity in Singapore to 120 MW when it is completed in end-2025.
The project is expected to have a power usage effectiveness (PUE) of 1.23. This metric refers to the ratio of energy used for cooling on top of the IT load, and a ratio of one indicates no additional energy used for cooling.
But with the shift toward AI, these workloads will consume more power. Experts note that there are new technologies in place to boost cooling efficiency.
In its roadmap outlining Singapore’s green initiatives for data centers, the Infocomm Media Development Authority (IMDA) noted that AI workloads will have higher rack densities, which refer to the amount of power used by a single rack cabinet in a data center. While the average server rack consumed 8.4 kilowatts (kW) in 2020, this could rise to over 100 kW per rack.
Air cooling – where servers are placed in air-conditioned rooms – can only support up to 20 kW per rack. Hence, more sophisticated liquid cooling solutions will be necessary to effectively cool higher-density racks.
Oliver Curtis, co-founder of AI cloud service provider Sustainable Metal Cloud, says that AI-enabled servers could be more power-efficient than traditional servers. This would enable Singapore to produce more output for the same amount of power capacity that it currently has.
The company has retrofitted existing data center capacity from ST Telemedia Global Data Centres to host AI servers that are immersed in thermally conductive liquid that removes heat more efficiently than air. This improves the firm’s PUE from 1.5 to 1.1, well below IMDA’s threshold of 1.3 for what is considered a “green” data center.
“That allows us to price our product as cheap as in the US, yet we’re doing so here in a much more high-cost environment,” Curtis adds.
Given energy constraints and the need to be sustainable, NTT Data Singapore CEO Png Kim Meng says that if there were an update to IMDA’s roadmap, he would like to see a deeper integration of green initiatives and advanced technologies such as AI.
“Enhancements should focus on expanding the scope of sustainable development practices within data centers, promoting energy efficiency, and reducing carbon footprints,” he said, adding that robust incentives and clear guidelines will incentivize more companies to invest in green technologies.
Competition from the region
BMI’s Lombatti said that because energy and power are scarce resources in Singapore, companies have looked to Malaysia’s Johor Bahru and Indonesia’s Batam to deploy capital, even if these markets are not as digitally mature.
Still, he noted that there is a broader risk that the explosive growth in these markets could lead to resource constraints as well.
Noorazam Osman, Johor Bahru’s city council mayor, said in May that data center investments should not compromise the state’s domestic water and power needs.
Lombatti says that regulators and governments may later realize the scale of the water and energy drained by data centers after they are built, only to implement regulations that create uncertainty for operators.
“They will likely introduce either a local ban, perhaps in a town or a specific region, or it can be a countrywide ban, where there is no more building activity,” he adds.
Bain’s Karunakaran points out that one factor in Singapore’s favor is that the regime offers businesses certainty. This likely contributes to the 20% premium that local data centers tend to draw.
He noted that data center operators in Indonesia have faced foreign ownership limits, along with significant currency risks and some potential difficulties in repatriating profits back to shareholders as dividends.
While the proportion of Southeast Asian data center capacity hosted in Singapore may fall, he does not expect the proportion of revenue generated by the country’s data centers compared to their regional counterparts to decline in the next three years.
Asher Ling, managing director of Singapore-based data center operator Princeton Digital Group, notes that IMDA’s roadmap helps to establish the guard rails for companies seeking new data center capacity.
Princeton Digital Group has been executing its SG+ strategy since 2023, to build data center campuses in Singapore, Batam, and Johor Bahru in collaboration with the Singapore Economic Development Board.
“We’re able to work collaboratively, symbiotically with Johor and Batam to create a larger region that really serves all the complex needs of the global community,” Ling says. “I think that really becomes a very interesting case study for the world to see in the next five years or so.”
