Today, those resources and energies are being turned toward AI.
On Feb 12, Prime Minister and Finance Minister Lawrence Wong announced a slate of measures to enable Singapore to harness AI and use it to “overcome our structural constraints — our limited natural resources, rapidly ageing population, and tight labour market.”
As part of that push, Singapore will set up a National AI Council, chaired by Wong. The council will, in turn, oversee a set of “National AI Missions” that Wong says will drive the implementation of AI across four sectors: advanced manufacturing, connectivity, finance and healthcare.
“Delivering this will require us to work differently. We will review regulations and create sandboxes, so that companies can test AI innovations safely and responsibly,” he says. “All this will require a coordinated national effort.”
See also: Co-working with AI
Companies will be encouraged to incorporate AI into their operations under a new “Champions of AI” programme. Wong says the government will provide tailored support to each company, including workforce training and enterprise transformation.
To support AI adoption, Wong is expanding the Enterprise Innovation Scheme to include AI expenditures as a qualifying activity eligible for a 400% tax deduction. Tax deductions are currently available for activities such as R&D, innovation and capability development.
A new AI park will also be established at One-North to help build up a community of AI practitioners and researchers. “This will be a new cluster to catalyse ideas, forge collaborations and translate AI initiatives into practical solutions for businesses and public services,” Wong says.
See also: Singapore lags global peers in AI returns despite matching adoption rates: report
This is on top of a broader push to reskill workers in AI. This involves building on SkillsFuture, an existing government initiative to encourage lifelong learning by providing subsidies for training courses. In addition to redesigning the SkillsFuture website to make AI training more accessible, the government will provide six months of free access to premium AI tools for Singaporeans enrolled in selected AI courses.
“AI is a powerful tool — but it is still a tool. It must serve our national interests and our people. We will define how AI is developed and used in Singapore,” says Wong.
Wong’s budget speech comes after an earlier series of announcements made by his Cabinet colleagues. On Jan 24, Digital Development and Information Minister Josephine Teo launched Singapore’s National AI R&D Plan (NAIRD) at the Singapore AI Research Week’s gala dinner.
As part of the NAIRD, Teo says Singapore will invest over $1 billion in three areas: driving fundamental AI research on issues such as safeguarding against AI risks and achieving resource efficiency, working with industry partners to adopt and deploy AI in their operations, and supporting young talent in their AI research endeavours.
“We aim to find new ways to gain efficiency across the tech stack — from chip architectures to model and application design,” Teo said at the Jan 24 launch event. “We aim also to build core AI engineering capabilities for the translation of theory to systems and applications.”
The NAIRD will run from 2025 to 2030 and is separate from earlier initiatives announced by the Ministry of Digital Development and Information (MDDI). In 2024, Teo said during her ministry’s Committee of Supply debate that the government would spend more than $1 billion over the next five years on AI. The money will go toward procuring AI compute resources and growing Singapore’s local AI talent pool and industry.
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“This vision is inspired by how we dealt with our water constraint — an existential risk for Singapore. Research over many decades helped build our water resilience, including reclaiming wastewater into what we call NEWater,” says Teo during the launch of NAIRD, while referencing the measures water-scarce Singapore took to achieve self-sufficiency.
Singapore is not just looking at investments in AI but also in the chips that power it. In December, Senior Minister Lee Hsien Loong announced Research, Innovation and Enterprise (RIE) 2030, the eighth instalment of Singapore’s five-year research and development masterplans. RIE2030 will run from 2026 to 2030 and will see Singapore commit $37 billion to its research and innovation efforts.
According to Lee, $3 billion out of the total RIE2030 budget will be used to support cross-cutting research and development programmes, including an initiative to grow the city-state’s semiconductor industry. Singapore produces 10% of the world’s chips and accounts for 20% of global semiconductor equipment output.
“AI is the biggest disruption the world has ever seen and definitely in Singapore’s history. This is something that requires an insane amount of attention across governmental departments and the business community here,” says Magnus Grimeland, founder and CEO of the early-stage venture capital firm Antler.
Before starting Antler in 2017, Grimeland was the co-founder and managing director of Zalora Group, a Southeast Asian e-commerce fashion platform.
“Given that it requires fewer people, the competitive position of Singapore within this technology shift is probably higher than ever,” Grimeland says of AI. “If I were to prioritise resources within the government for the next few years, I would put an even bigger effort into this. I think it’s going to be well worth it in the long run. This is a huge opportunity.”
Singapore’s big bucks aren’t that big
To be sure, the Singapore government’s investment in AI, while sizeable, is a drop in the ocean when compared to the amounts being spent by US tech giants. In January, social media giant Meta Platforms Inc says it expects to spend up to US$135 billion ($172 billion) on AI-related capital expenditures. That is nearly double the US$72 billion the company spent in 2025.
“As we plan for the future, we will continue to invest very significantly in infrastructure to train leading models and deliver personal super intelligence to billions of people and businesses around the world,” Meta Platforms’ CEO and founder Mark Zuckerberg told analysts during an earnings call on Jan 28.
The numbers are staggering once you consider the amount of capital being splurged on AI globally. Consulting firm McKinsey estimates global data centre investments to reach nearly US$7 trillion by 2030.
That’s not forgetting the national efforts underway in other countries that want to secure a foothold in AI, too. For instance, South Korea’s government has been running a tournament to identify the nation’s top AI leaders. The tournament has attracted a diverse group of participants, including start-ups and the subsidiaries of conglomerates LG and SK Group. The tournament will end in early 2027 and two winners are expected to be announced then.
The intense competition, however, should not deter Singapore’s ambitions, says Ben Leong, an associate professor of computer science at the National University of Singapore (NUS). “The US is not just the powerhouse of technology today. They have been the powerhouse for the last 20 years. For all the political issues they have, it is a very innovative market,” Leong says.
“That’s not to say that we shouldn’t care. We don’t have a choice. It is not possible for us to be Number One or Number Two in AI. Despite this situation, what can we do? Give up? That cannot be right. So we try to find niches that make sense for us.”
It’s not about size
One such niche would be Singapore’s foray into responsible AI frameworks that will guide how companies deploy the technology. According to Qualtrics’ 2026 Consumer Trends Report, 68% of Singapore consumers see AI as a positive for society, but only 40% of them trust organisations to use AI responsibly.
“That trust gap is a real challenge, and countries that solve both trust and adoption at scale will win, regardless of who builds the biggest model,” says Raen Lim, Qualtrics’ managing director for the Asia Pacific and Japan, citing the work done by AI Singapore, a national AI programme funded by the National Research Foundation.
Some innovations that have emerged from AI Singapore include Sea-Lion, a large language model designed to understand languages and cultures from Southeast Asia. In January, MDDI launched the world’s first Model AI Governance Framework for Agentic AI. MDDI says the framework is designed for companies looking to navigate the risks of deploying agentic AI in their work.
“These are solving real problems that impact real people and improve experiences for Singapore residents,” Lim says of these innovations. “The focus on responsible AI research addresses the trust gap that’s holding back adoption — and that’s exactly what businesses need to move from experimentation to real value creation.”
EY Asean data and artificial intelligence leader Manik Bhandari says Singapore can make the best use of its capital by adopting a focused approach when placing its bets on AI. “For a small and open economy like Singapore, leverage comes from deploying the investment in ways that create economy-wide spillovers rather than isolated wins.”
Instead of spreading their bets across different areas, Bhandari says Singapore should identify a few big bets and increase the ticket sizes on each. For instance, the city-state can choose to focus on specific high-growth AI projects and companies.
“This approach can improve the odds of producing a breakout success, whether a sovereign AI system for critical public sector functions or a globally competitive AI start-up,” he adds.
In fact, Singapore may not even need to break the bank to grow its own local AI champions. Antler’s Grimeland says that, instead of investing, both Singapore’s government and its largest companies can choose to be their clients. “For AI companies in their early days, if you want them to take off, then the government and the biggest companies in Singapore need to be their first customers.”
By regularly publishing problem statements for areas they want to use AI to solve, the government can encourage AI companies to develop solutions before becoming their first customer. “Once you have the first customer up and running and if it’s a recognised customer like the Singapore government or a big company, that will really help them accelerate and grow,” Grimeland adds.
Unlike past technological revolutions, Singapore’s small size will not limit its ability to nurture thriving AI businesses. “When you look at AI, you can build really big companies with fewer people, which is very advantageous to Singapore,” says Grimeland.
“Back at Zalora, we hired 3,000 people in three years and that’s a bit of a nightmare to do in Singapore because there just aren’t that many people. We had to hire a lot of them in Malaysia, Indonesia and other parts of Southeast Asia,” Grimeland says. “But if you are building for AI, you can build a billion-dollar company with 1,000 people and that’s very well set up for the Singaporean ecosystem.”
Singapore Inc meets AI
That’s not to say only new players, such as start-ups, will be able to leverage the AI boom. Incumbent players, such as Singapore’s local banks and government-linked companies, can achieve higher valuations by positioning their businesses accordingly.
According to a Jan 27 report by OCBC Group Research analysts Chu Peng, Ada Lim and Andy Wong, Singapore’s AI growth differs from the US and China in that it is infrastructure-led. This presents an opportunity for companies building the foundational infrastructure for AI, such as data centres, fibre connectivity, semiconductors, power and cooling.
OCBC sees Keppel DC REIT (SGX:AJBU
) (fair value: $2.66), Mapletree Industrial Trust (SGX:ME8U) (fair value: $2.33), CapitaLand Ascendas REIT (SGX:A17U) (fair value: $3.32), Stoneweg Europe Stapled Trust (SGX:SET) (fair value: EUR1.87) and CapitaLand India Trust (SGX:CY6U) (fair value: $1.42) as key beneficiaries of the growth in investor interest for data centres.
When it comes to power, the bank is optimistic about utility and energy-related counters such as Sembcorp Industries (SGX:U96) (fair value: $8.02), Keppel (SGX:BN4) (fair value: $11.90), Keppel Infrastructure Trust (SGX:A7RU) (fair value: $0.53) and Hong Leong Asia (SGX:H22) (fair value: $3.10). As for communications services, OCBC sees upside from investing in Singapore Telecommunications (SGX:Z74) (fair value: $5.75) and NetLink NBN Trust (SGX:CJLU) (fair value: $1.05).
Shares for Singapore Telecommunications have doubled since 2024 and received an added push after it announced on Feb 4 that it was teaming up with KKR to take full ownership of ST Telemedia (STT) Global Data Centres (GDC). STT GDC’s network of 100 data centres spans across a dozen markets and has a total capacity of 2.3 GW.
Analysts received the deal positively, including PhillipCapital’s Paul Chew (target price: $5.35), Maybank Securities’ Hussaini Saifee (target price: $5.08), and DBS Group Research’s Sachin Mittal (target price: $5.71).
What makes the Singtel data centre proposition interesting is not merely the leasing of Graphics Processing Unit (GPU) capacity. Singtel is piloting a GPU-as-a-service (GPUaaS) offering, allowing enterprise customers who do not want to invest in their own processing capacity to lease such capabilities on a need-to basis.
From the perspective of Da Wei Lee of Morgan Stanley, Singtel, via its multinational Bridge Alliance, has the platform to launch this GPUaaS offering across the region. He points out that Singtel’s Digital Infraco business is shaping up to be a key growth driver. However, it is now valued at zero by the market because it is still in the build phase and its contribution to Singtel’s ebitda is still in the single digits. Lee estimates that GPUaaS could lift its ebitda 1% to 4% with 10,000 to 20,000 GPUs at 30% to 50% ebitda margin.
Separately, OCBC says Singapore companies in the industrial and financial sectors can benefit from AI. Among industrial names under its research coverage, OCBC sees upside in Singapore Technologies Engineering (SGX:S63) (fair value: $10.90), Singapore Post (SGX:S08) (fair value: $0.43), ComfortDelGro Corp (SGX:C52) (fair value: $1.74), and Boustead Singapore (SGX:F9D) (fair value: $2.02). In terms of financials, OCBC says its peers, DBS Group Holdings (SGX:D05) (fair value: $55.00) and United Overseas Bank (SGX:U11) (fair value: $38.20), will benefit from deploying AI.
Maybank Securities, meanwhile, expects local tech stocks such as AEM Holdings (SGX:AWX) , Frencken Group (SGX:E28) and UMS Integration (SGX:558) to benefit from AI tax deductions, which will drive capex and equipment demand. Under the expanded Enterprise Innovation Scheme announced at the Budget, businesses can claim an annual tax deduction of 400% on qualifying AI expenses, capped at $50,000 per year, for the upcoming Years of Assessment 2027 and 2028.
Of course, some investors have expressed scepticism over whether AI will live up to all the hype. Hedge fund manager Michael Burry took a short position against chip giant Nvidia before de-registering his own fund, Scion Asset Management, in November 2025. For Burry, the AI boom is but a “glorious folly.”
Leong, the NUS don, says there is no doubt that AI has raised productivity. It is just that the mileage companies can earn from it will vary depending on the nature of their work. “The reality is that AI has somewhat increased productivity, about 20% to 30%. It’s not massive, but there are some productivity gains. But if you ask me, will AI change everything? Not really or perhaps not so fast.”
EY’s Bhandari notes that the adoption of AI remains uneven amongst companies. To address this, he recommends that policymakers focus on raising AI literacy nationwide, not just within companies. For instance, Singapore’s government can distribute “AI vouchers” to encourage Singaporeans to sign up for AI tools or training. The vouchers can be designed in the same vein as the Community Development Council (CDC) vouchers, which were given to offset cost-of-living pressures.
“One moonshot idea is embedding AI literacy from early school years so students learn how to incorporate AI in learning and coursework, which will involve updating curricula, training educators and rethinking pedagogy,” Bhandari says. “Early exposure will help create a future-ready, AI-savvy workforce for Singapore.”
Ultimately, a company’s pace of AI adoption will depend on its management’s decisions, rather than the sector it operates in. “If management is clever, any industry can make it through, though some are more amenable, for example, like logistics. Those are industries dealing with a lot of volume, a lot of brain-dead work, checking and finding data that sort of thing,” NUS’s Leong says.
“Adoption of AI is not a tech problem. It’s a human problem where you are trying to change behaviour.”
