The article suggests that Singapore should pursue its own AI development strategy, focusing on advantages in systems, governance, and deployment capabilities rather than competing on scale with global superpowers.
Prime Minister Lawrence Wong emphasized that Singapore will harness the power of AI on its own terms, rather than blindly following the global technology race.
The author notes that companies like China’s Kimi and Japan’s Sakana AI demonstrate that smaller countries or organizations can still compete by changing their approach instead of matching investment scale.
Singapore places people at the center of its AI transformation, balancing the speed at which AI changes jobs with the pace at which workers adapt to new roles.
The country aims to train 100,000 “AI bilingual” workers—combining AI literacy with domain expertise to boost productivity.
Due to workforce constraints, AI is viewed as a solution to enhance productivity for nurses, engineers, technicians, and small businesses rather than merely replacing labor.
The article proposes that Singapore leverage its small size to build integrated national-level AI systems, connecting regulators, research institutes, enterprises, investors, and tech corporations to shorten the time from testing to deployment.
The AI Missions announced in Budget 2026 are seen as the foundation for building shared AI infrastructure, allowing multiple organizations to securely share and exploit data while retaining control.
Singapore is expected to become a testing ground for practical AI systems in healthcare, finance, and transportation, thereby developing exportable software, AI models, safety assurance tools, and operational workflows.
ASEAN is identified as the primary expansion market. As ASEAN Chair in 2027, Singapore can validate its AI deployment capabilities in a multilingual, multi-regulatory environment with varying levels of development.
The author concludes that Singapore’s competitive advantage will stem from turning scale limitations into a strength in building trustworthy AI systems capable of widespread global deployment.
📌 Singapore does not need to compete head-to-head with AI superpowers in capital or model scale. Instead, it should focus on training 100,000 AI-skilled workers, building integrated national-level AI systems, and turning proven solutions in sectors like healthcare, finance, and transportation into exportable products. If successful in Singapore and ASEAN, these models can become reference standards for many other nations.
