New Research from ST Telemedia Global Data Centres Reveals Asia’s AI Ambitions Hampered by Infrastructure and Talent Gaps
- Written by Media Outreach
High adoption, limited readiness across Asia
The report reveals that AI ambition across Asia is high, with nearly 90% of organisations having embarked on their AI journeys. However, a significant 71% remain in the "Builder" stage of maturity, where initial AI pilots struggle to scale into production environments capable of delivering consistent and measurable return on investment (ROI). In contrast, only 17% of organisations are considered "future ready", having invested in scalable infrastructure, mature data governance and specialised operational expertise, highlighting a widening readiness gap across the region.
Challenges faced by the Builders
Across Asia, the research identifies a reinforcing cycle that keeps many organisations stuck in pilot mode. AI initiatives are often launched on infrastructure that cannot scale to production, limiting their ability to demonstrate measurable ROI and making it harder to justify further investment in purpose-built, high-density environments. This challenge is compounded by gaps in in-house expertise, with many organisations lacking the specialist operational skills required to manage increasingly complex AI infrastructure at scale.
"Across Asia, organisations are moving quickly from experimentation to implementation, but many are discovering that AI success now depends less on training models and more on foundations," said Chris Street, Group Chief Revenue Officer of ST Telemedia Global Data Centres. "Without scalable infrastructure and operational readiness in place, it becomes difficult to convert early AI ambition into consistent business value."
The Sustainability Blind Spot
Despite rising energy and cooling demands driven by AI workloads, sustainability considerations remain secondary for most organisations when evaluating infrastructure options. Although 27% of organisations say ESG goals will actively shape or be central to their future plans, 64% of organisations across Asia continue to prioritise performance or cost, even as power density, thermal efficiency and long‑term total cost of ownership become increasingly critical factors in scaling AI responsibly.
A disconnect between what organisations want and what they need
The study also highlights a persistent disconnect between how organisations evaluate infrastructure partners and the capabilities they actually need to scale AI. Across Asia, organisations continue to prioritise baseline requirements like security and reliability, despite identifying operational expertise, scalability and cost efficiency as their most significant challenges.
Singapore: ahead of the region, but facing a new constraint
These challenges are visible across the region, but they manifest differently in more mature markets. Singapore stands out against the regional baseline with a significantly larger share of organisations having progressed beyond early-stage pilots. While only 17% of organisations across Asia are considered future‑ready, 40% of Singapore organisations have reached the Integrator stage, reflecting stronger early execution and deployment capability.
However, the study also finds that the final step to leadership remains the most difficult. Only 3% of Singapore organisations have reached the "Leader" stage of AI infrastructure maturity, signalling that even in Asia's most mature AI market, the transition from integration to full leadership remains difficult.
Scaling, not adoption, is now the key challenge
In Singapore, where adoption is more advanced, the constraints have shifted. Limited infrastructure headroom, shortages in specialised operational expertise and continued investment discipline are now emerging as the primary barriers to scaling AI workloads and sustaining leadership.
"For Singapore, AI adoption is relatively mature; the defining challenge now is scaling deployments fast enough to support real‑world demand," said Mingcheng Lim, Country Head – Singapore, ST Telemedia Global Data Centres. "Whether the country can maintain its lead in the region will depend on whether infrastructure capacity, specialist expertise and investment approaches can evolve at the same pace as AI workloads."
Sustainability awareness has yet to shape infrastructure choices
In Singapore, regulatory expectations have driven relatively high awareness of sustainability issues. However, sustainability continues to rank among the lowest priorities when organisations evaluate infrastructure providers, highlighting a gap between awareness and action, even as power density, thermal efficiency and long‑term cost efficiency become increasingly important to scaling AI responsibly.
The mismatch between wants and needs persists
As with the wider region, Singapore organisations continue to evaluate infrastructure providers based on familiar baseline criteria, even as their scaling challenges point to a growing need for specialist expertise, speed to scale and sustainable, high‑density infrastructure capability.
These findings suggest that Asia's next phase of AI progress will be defined not by ambition alone, but by execution capability. For Singapore, sustaining regional leadership will depend on infrastructure strategies that support scale, resilience and speed, enabling organisations to convert early AI momentum into enduring competitive advantage.
To download the report, Mind the Gap: Bridging the AI Infrastructure Readiness Divide, please visit: https://www.sttelemediagdc.com/resources/ai-readiness-assessment-report.
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