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Many organisations have already moved beyond asking whether AI matters. Across Asia, the more pressing question is whether they are equipped to run it reliably at scale. As AI shifts from experimentation into operational use, competitive outcomes are being shaped less by ambition alone and more by the infrastructure, operating models and specialist capabilities that support deployment in production. This is where the next divide is emerging.

Infrastructure limitations, capability gaps, long build timelines, and fragmented decision-making rarely exist in isolation. They reinforce one another, creating compounding friction that becomes most visible at the point where AI initiatives need to scale. Progress slows not because any single constraint is insurmountable, but because the system to move forward in a coordinated way.

ST Telemedia Global Data Centres’ regional study, Mind the Gap: Bridging the AI Infrastructure Readiness Divide, establishes how Asia’s AI journey has moved beyond early experimentation. Across markets, organisations are actively piloting new use cases at pace.

Findings from ST Telemedia Global Data Centres’ inaugural Mind the Gap: Bridging the AI Infrastructure Readiness Divide report brings this into focus. Across the region, AI ambition is widespread: nearly 90% of organisations in Asia have already embarked on their AI journey, but most are struggling to move beyond experimentation.

While nearly 90% of organisations across the region have initiated AI efforts, momentum is increasingly stalling where it matters most: turning pilots into measurable business value. As AI matures, success is no longer defined by experimentation, but by the ability to execute at scale.

Singapore’s vision of becoming a leading digital hub depends on the strength of its trusted digital infrastructure, with data centres sit at the core. These facilities power cloud services and digital platforms across critical sectors from finance and healthcare to logistics and public services. As organisations scale their adoption of artificial intelligence (AI), the underlying infrastructure must keep pace: AI workloads drive higher power density, greater cooling needs, and increased operational complexity. At the same time, Singapore must stay on track with its national climate commitments.

STT Singapore 5 is located in the east of Singapore with rich connectivity and abundant redundant power availability.

Artificial intelligence (AI) workloads are putting new pressures on data centre designs and systems.

Artificial intelligence (AI) is quickly becoming a vital business tool that is transforming organisations across industries, from healthcare and finance to manufacturing and mobility. This transformation has been especially pronounced in Asia Pacific, with research indicating that countries such as Singapore, Australia, New Zealand and South Korea are outpacing most North American and European markets in enterprise AI adoption.

In 2025, we expanded access to AI-ready capacity, high-performance cooling and more sustainable solutions across our global platform – strengthening the foundation for organisations building and scaling digital services. Here’s how these developments translate into value for your business.

Southeast Asia stands at a pivotal crossroads: to be architects of its digital future or outsource the development of its digital backbone. The answer lies not in the mere pace or scale of data centre growth, but in how deeply these investments are integrated into national competitiveness strategies.

The Singapore Green Data Centre Roadmap outlines a bold vision for sustainable digital infrastructure, supported by initiatives aimed at accelerating energy efficiency and the adoption of green energy across the data centre sector. Yet, challenges such as complex procurement processes and the high cost of imported green energy remain.