SINGAPORE — Prime Minister Lawrence Wong called for Singapore to organise nationally around the responsible use of artificial intelligence, saying the country will set clear rules for how the technology is developed and applied and warning against paralysis in the face of uncertainty.
Wong’s remarks set out a deployment‑first approach: prioritising safe, effective use of AI at speed, rather than pursuing the largest so‑called frontier models. He framed the push as a way to address domestic constraints while ensuring the gains from automation and discovery are broadly shared, positioning AI as a core pillar of Singapore’s next phase of economic strategy and public‑sector modernisation.
Confronting risks without stalling progress
Wong acknowledged public unease over job losses, false information and ethical harms linked to powerful systems, saying these concerns “are real and must be confronted squarely.”
“But fear cannot be Singapore’s response,” he said. He added: “And we will ensure that its benefits are shared widely across society,” he said.
“If we allow uncertainty to paralyse us, we will fall behind in a world that is moving rapidly ahead.”
He said how AI is developed and used in Singapore “will be defined, with clear rules set to ensure it is applied responsibly and safely.” Those rules, he suggested, will build on the government’s existing model of technology regulation: principles‑based, risk‑tiered and closely aligned with global best practice under the Model AI Governance Framework.
Key points Wong highlighted:
– Risks that require active management: job displacement, misinformation and the ethical use of powerful technologies, particularly in high‑stakes domains such as finance, healthcare and public services.
– Public commitments: define clear rules for responsible and safe use; ensure benefits are shared widely through support for workers in transition, skills upgrading and inclusive access to AI‑enabled services.
– National purpose: apply AI to help overcome limited natural resources, a rapidly ageing population and a tight labour market, while sustaining Singapore’s competitiveness as a trusted node in the global digital economy.
Deployment over frontier model building
Wong said Singapore’s advantage “does not lie in building the largest frontier models, but in deploying AI effectively, responsibly and at speed.” He argued that the country can compete by moving quickly on real‑world applications, governance and integration across sectors, from logistics and advanced manufacturing to public healthcare and city management.
That stance aligns Singapore more closely with countries that emphasise applied innovation and standards‑setting over sheer computing scale, and underscores the role of the state as both regulator and major customer for AI systems.
He described a role for the country as a convening point for innovation: “Singapore can be a trusted hub where companies and researchers come together to develop, test and deploy impactful AI solutions, and do so faster and more coherently than many larger countries,” he said. Officials see that convening role extending to cross‑border data flows, AI safety benchmarks and interoperable governance regimes.
Industry activity cited by Wong
Wong noted that companies such as Google and Microsoft have set up AI centres of excellence in Singapore, which he said are creating a growing number of jobs for Singaporeans. He presented the corporate investments as evidence of demand for a jurisdiction that can pair technical ambition with clear guardrails and stable policy, pointing to emerging clusters in areas such as financial AI, cybersecurity and enterprise productivity tools.
He also indicated that the government will deepen collaboration with industry on standards, testing and talent development, so that regulatory expectations are clear early in the innovation cycle rather than imposed only after systems are widely deployed.
From pilots to a nationally coordinated push
Beyond individual proofs of concept, Wong said Singapore must move past “individual pilots and isolated experiments.” The aim, he said, is coordinated action at scale across institutions and sectors so that promising tools become widely used solutions, not one‑off showcases.
That will require public agencies, regulators and industry to align on common infrastructure, data‑sharing safeguards and evaluation metrics. It also means embedding AI into core government operations, rather than treating it as a peripheral innovation agenda.
“We must organise at a national level, and move with speed and scale,” he said, signalling that forthcoming national AI initiatives will be framed not only as a technology agenda, but as a broader exercise in economic restructuring and public‑policy reform.
Related reading
