Singapore will set up a new National AI Council chaired by Prime Minister Lawrence Wong to steer policy, align government agencies and push the city-state’s next phase of artificial intelligence adoption, Wong said in his Budget 2026 statement.
Wong said the government would “review regulations and create sandboxes” so firms can test AI innovations “safely and responsibly”, while better coordinating research and development, regulation and investment promotion so agencies “act in concert”.
The prime minister, who is also finance minister, said Singapore wants AI to move beyond pilots and isolated experiments, announcing a new set of “national AI Missions” aimed at AI-led transformation in four sectors: advanced manufacturing, connectivity, finance, and healthcare.
Wong cautioned that meaningful AI transformation is difficult even for large multinationals, requiring companies to organise data, rebuild systems, redesign processes and jobs, and retrain workers.
He pointed to DBS and Grab as examples of Singapore companies moving decisively, and announced a new “Champions of AI” programme to support firms seeking end-to-end business transformation using AI.
To broaden adoption, Wong said Singapore will expand the Enterprise Innovation Scheme, which provides businesses with 400% tax deductions on qualifying expenditure, to include AI spending for the Years of Assessment 2027 and 2028, capped at S$50,000 per year of assessment.
He also said the Productivity Solutions Grant will be expanded to support a wider range of digital and AI-enabled tools for companies of all sizes.
The move builds on Singapore’s wider push to strengthen national AI capabilities, including government plans announced in January to invest more than S$1 billion in public AI research through 2030.
By putting the prime minister at the helm and naming mission sectors, Singapore is signalling that AI is now treated as economic infrastructure, not just a tech policy file, with a focus on execution, faster diffusion into industry, and regulatory pathways that reduce uncertainty for deployment.
The main test will be whether smaller firms can move from point solutions to genuine workflow redesign, given data readiness constraints and talent bottlenecks.
