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Digital Realty targets $5.4b Singapore AI expansion

Digital Realty is targeting nearly S$7 billion (US$5.47 billion) in total investment in Singapore, as it expands capacity for AI-related demand in Asia-Pacific.

The company said it is including more than S$4.3 billion (US$3.36 billion) in new developments and ongoing investments,

Its Singapore workforce has risen to more than 300 and could reach 400 by 2030.

The company also plans to launch an Innovation Lab in Singapore in H2 2026 to support AI testing.

🔗 Source: Digital Realty

🧠 Food for thought

Implications, context, and why it matters.

The investment targets tightly controlled, newly opened data center capacity

  • Digital Realty’s planned investment tracks Singapore’s decision to open new data center capacity after a moratorium, a temporary halt on new approvals, that began in 2019 1.
  • The Singapore government will allocate at least 200 megawatts (MW) of data center capacity through a new program, while operators must use approved green energy pathways and prove economic benefits to qualify 2.
  • Digital Realty Innovation Lab plans to test setups of up to 150 kilowatts (kW) per cabinet, which tackles the power demands of high-density AI workloads 3.
  • New AI chips now demand far more power than older facilities can handle, which raises the need for liquid cooling, which uses fluid instead of air to remove heat, in high-density builds 4.

Singapore’s rules are shaping AI data center design

  • Singapore’s strict oversight is steering operators toward advanced, energy-efficient designs, with capacity awards tied to sustainability and economic value requirements 5.
  • Methods like liquid cooling and AI-powered energy management could spread to other cities with tight land and power limits 6.
  • Limited space and heavy competition in Singapore are pushing some projects to nearby sites like Johor Bahru, Malaysia, and Batam, Indonesia, for less critical workloads 1.
  • The pattern supports a regional hub-and-spoke model where Singapore runs the highest-value computing workloads, while nearby locations absorb overflow demand 1.

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