Small AI Investment in Asia: Infrastructure Gaps Reshape Growth Strategy

Smaller economies see strategic opportunity in targeted AI adoption, despite resource constraints.

Small AI investment in Asia is gaining momentum as regional leaders rethink infrastructure needs and resource constraints. At the Fortune Innovation Forum in Kuala Lumpur, experts highlighted that AI costs remain high due to processors, data centers, power, water, and data acquisition. While global giants can finance these requirements, Southeast Asia faces significant barriers to scaling AI systems.

Mahesh Uttamchandani, regional practice director for digital for East Asia, South Asia, and the Pacific at the World Bank, described a developing opportunity for smaller nations. He emphasized the role of “small AI”, which remains targeted, potentially offline-capable, and independent from large-scale AI architectures that dominate innovation in major economies. This direction signals a shift toward sovereign AI suited for local requirements and resource profiles.

Growing momentum for sovereign models

Jon Omund Revhaug, Asia head for Telenor, noted that there is “ample opportunity” for countries to pursue sovereign AI. Singapore, Malaysia, and Thailand are already working on custom models aligned with local needs while expanding data infrastructure and regulatory frameworks.

However, Lionel Yeo, Southeast Asia CEO for ST Telemedia Global Data Centers, stressed that expansion depends on building more power capacity to support deployment. He explained the urgent need for collaboration across the supply chain to secure electrical power from generation through to distribution.

Resource constraints drive regional collaboration

Water availability is also affecting the pace of growth. Singapore temporarily paused data center construction in 2019 due to water consumption concerns. Meanwhile, the Malaysian state of Johor expects continued water constraints through mid-2027 while still seeking investment-driven AI infrastructure expansion.

Uttamchandani suggested that shared access across borders could become a practical model as not every country needs its own data centers. Regional cooperation could increase resilience through shared power and water resources when planning data-center infrastructure.

Talent shortages limit infrastructure scale

Workforce availability represents another challenge. Wendy Tan White, CEO of Intrinsic, highlighted shortages in skilled labor needed to assemble servers and manage hardware-level integration. She noted that some tasks, such as cable handling, remain entirely manual without automation alternatives.

Despite barriers, White identified opportunity. Asia holds manufacturing strength and regulatory flexibility at a time of geopolitical tension and population shifts. Strong public policy could position the region for leadership in AI governance and sustainable technology legislation.

Regulatory actions shape competitive feasibility

Governments are taking early steps. Uttamchandani cited a recent development in the Philippines that removed legislative approval requirements for telecom market entry. Updating legacy regulation may unlock access and accelerate deployment cycles.

Even with reforms, demand will exceed supply. As Yeo noted, the infrastructure and talent pipeline will not match acceleration needs. Businesses must adapt by building efficiency into AI deployment rather than expecting capacity expansion to resolve constraints.

Strategic viewpoint

The message is clear: Small AI investment in Asia could deliver meaningful impact when combined with focused resource allocation and policy alignment. The region may transform constraints into opportunities through collaboration, sovereign innovation, and infrastructure modernization.

Discussion Question

How can smaller economies balance AI development ambitions with resource limitations without relying on large-scale global systems?

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