National AI Strategy 2.0: Refreshed Priorities
This document outlines Singapore's refreshed National AI Strategy (NAIS) priorities across ten enablers to accelerate AI adoption, build deep research capabilities, nurture talent, and foster a trusted environment. It introduces national AI Missions focused on advanced manufacturing, financial services, connectivity, and healthcare to drive sectoral transformation. Furthermore, the strategy emphasizes ecosystem integration, data governance, resource-efficient compute, and international leadership.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Policymakers, industry leaders, researchers, and practitioners interested in Singapore's national approach to artificial intelligence development and governance.
What the document contains
The document covers Singapore's updated strategic priorities across ten key enablers—Industry, Government, Research, Talent, Capabilities, Ecosystem Integration, Compute, Data, Trusted Environment, and Leader in Thought and Action. It details national AI missions, public sector AI adoption, R&D funding, workforce upskilling programs, data governance, and international collaborations.
It does not establish legally binding horizontal AI legislation or punitive enforcement mechanisms within the text itself, relying instead on voluntary frameworks, guidance, and sector-specific regulations.
- Singapore refreshed its National AI Strategy priorities across ten core enablers to adapt to rapid developments in AI technology and governance.
- National AI Missions have been established in four priority sectors: Advanced Manufacturing, Financial Services, Connectivity, and Healthcare.
- The strategy commits over S$1 billion through the updated National AI R&D Plan to boost public AI research and talent development from 2025 to 2030.
- Workforce transformation initiatives target upskilling workers to become AI bilingual and expanding AI literacy across the economy.
- Singapore continues to pioneer practical governance through tools like model AI frameworks, testing frameworks, and international safety collaborations.
· Foreword · Introduction · Refreshed Enablers - Industry - Government - Research - Talent - Capabilities - Ecosystem Integration - Compute - Data - Trusted Environment - Leader in Thought and Action · The Work Ahead: Building an AI Hub
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Adoption will also be underpinned by refreshed policy guidance on the use and deployment of Generative AI, which takes a balanced, risk-based approach with stronger expectations around data security, accountability and oversight for higher-risk use cases.
GOVERNMENT
screening score · 2026-10-23
Fairness
1/5Non-discrimination and equitable treatment
Entrench broad-based AI capabilities to support inclusive growth.
CAPABILITIES
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
screening score · 2026-10-23
Human Oversight
4/5Humans remain in control of consequential decisions
AI can be deployed to augment healthcare professionals’ diagnoses and support clinical decisions.
INDUSTRY
screening score · 2026-10-23
Privacy
4/5Protection of personal data and private life
The PET Sandbox has facilitated nine real-world use cases across finance, healthcare and advertising, demonstrating that privacy-preserving data sharing is practically achievable.
DATA
screening score · 2026-10-23
Transparency
4/5Openness about how AI systems work and are used
The AI Verify Testing Framework was extended to cover Generative AI risks, and the Starter Kit for Testing LLM-Based Applications was finalised in 2026.
TRUSTED ENVIRONMENT
screening score · 2026-10-23
Enforcement
4/5Consequences and compliance mechanisms with real force
We will not hesitate to regulate or legislate where necessary and effective.
TRUSTED ENVIRONMENT
screening score · 2026-10-23