How Singapore's AI strategy became a roadmap for other nations

The panel examines Singapore as a test case for small and mid-sized countries. Experts argue Singapore cannot compete with China and the US on scale, so it bets on talent and a regulation environment that encourages innovation. Andrea Phua explains the systems-level view: making industries more competitive, delivering government services better and helping citizens understand the technology.

Simon Chesterman pushes back on training everyone as a coder — what matters is enabling the whole economy to spot AI opportunities, more like electricity than computer science. Shameek Kundu stresses pragmatism: AI Verify is built to help small and mid-sized firms adopt AI safely, not to add boxes to tick. Serena Marchetti notes Canada, India, Israel, Germany and France compete strongly on different dimensions of the index.

On the data point that Asia outside China and the US holds just 2.6% of private AI investment, panellists argue Asia favours value extraction over fundamental model research, and that renting compute often beats building it. Singapore makes 20% of global semiconductor equipment and 10% of chips, but its strategy is to secure diversified compute supply rather than lock in to one vendor.

Caption language: en · Fetched: 2026-05-02

if I think about how we came out of the strategies across government uh it's really thinking about AI from a systems level approach it's not about using AI for AI sake it is about making our Industries more competitive uh delivering government services better and helping our citizens also understand and interact with this technology in a way that builds confidence and Trust now if the first session uh with clay and the minister was about Singapore as a as a global uh AI Powerhouse as I mentioned in the introduction we're now going to talk about the extent to which Singapore can be used as a test case for small and medium tier countries and Simon I'm going to start with you um we've heard mention that for such a small country Singapore really does punch above its weight in terms of AI investment and Innovation what lessons should other small and midsize countries maybe the ones we've just seen on the global AI index take uh from Singapore's success in this area yeah well I think it was pretty clear from the outet that a country like Singapore could never compete with China and the United States in terms of scale so if you can't beat them on quantity you can at least try and compete on quality and so we've really invested in talent and in a regulatory environment that encourages Innovation and I think that's maybe something that Singapore is at least an interesting experiment that in contrast with the kind of Eur European approach where it's often a kind of oppositional mentality how do we hold back how do we protect the rights that um might be at stake that's one approach uh the American approach of very hands-off how do we sort of just fan the Flames of the free market uh or the Chinese approach where it's very much State controlled here it's very much intended as a partnership uh and so you make a virtue of small size you make a virtue of having a highly connected Highly Educated digital population and a small environment where you can organize events like this where you get The Regulators the industry and the the think tanks around the same table to try and craft a whole of nation strategy that gets everyone aligned on how to take advantage of the digital economy while minimizing or mitigating the risks um and Shmi before I ask you a question I believe you've got a new title as of yesterday that we want to congratulate you on thanks yeah as of yesterday I've just joined as the head of the AI verify Foundation which those of you from Singapore know um and I guess the the relevant aspect thank you the relevant aspect to Simon's point is I think Simon you mentioned about about openness and about a regulatory environment that is encouraging of innovation so the AI verifi foundation for example takes the approach around AI testing and safety that it shouldn't just be something that people take boxes against or something that people do because they're asked to do instead how do we make it a forum U toolkit that allows companies particularly smaller and mediumsized companies to adopt AI so you go from one end which is hey use AI safely or otherwise don't use it to the other angle which is actually how can we help you adopt AI safely through tool gate so I think that's a continuation of that theme about encouraging regulatory environment and Andrew I'm going to come to you in one second but before before I do um Serena I wanted to ask you from your research um are there any small midsize companies that you expect to be shooting up the rankings soon to compete with Singapore I would say yeah definitely um there are a lot of other uh countries that I've mentioned earlier also uh during the presentation that are sort of smaller but also really Dynamic AI hubs um for different reasons for example when it comes to Talent Germany France and Canada are quite high on the index um when it comes to investment uh Israel and uh Canada again and Korea are also very strong strong performers uh in infrastructure uh Canada and India uh as well we expect to uh rank a bit higher um so yeah it really it really varies and I guess it depends on when you look um but yeah definitely there are other countries aside from uh Singapore and Andrew we were talking backstage and Serena was saying and correct me if I'm wrong that Singapore has gone up six places in 3 years on the global ranking list I wonder I'm interested in your Insight on how it has achieved that Ascent really in a relatively short period of time what can you pinpoint there um I think if I think about how we came out the strategies across government uh it's really thinking about AI from a systems level approach it's not about using AI for AI sake it is about making our Industries more competitive uh delivering government services better and helping our citizens also understand and interact with this technology in a way that builds confidence and trust and what does that look like when you talk about helping citizens understand tangibly what are you doing to make that happen so we spend a lot of effort uh Skilling our Workforce uh telling them about the new technologies and skills that are required to do better in the workplace uh we spend a lot of time engaging with Industries and companies to to talk about the job redesign that needs to happen so that people uh can use these Technologies effectively with our seniors and with our schoolgoing children we spent a lot of time too telling them about some of the ill effects of using AI poorly uh or using it wrongly uh and that I think goes a long way into um helping people understand what it should be used for and what it shouldn't be used for and what are some of the things that you need to you know be aware of as you're dealing uh in the online space um so these are some of the ways in which we try and educate build awareness uh and also put in place safeguards and and guard Wheels um that ultimately tries to promote the use and the investments in it uh and not sort of stifle The Innovation even as we care about these important matters of Safety and Security this is I can add to Andrea's Point uh Singapore also really uh invested in its research ecosystem if I remember right uh from last year Singapore's um uh research and development spend per capita was something like 18 times higher than the one of the US which I think says a lot um a few of you have mentioned talent and investment in Talent being a key reason for Singapore's success if any of you were advising the governments of France or Denmark one of those countries in the middle of the list what would you be telling them they should be doing with their talent investment what should it be looking like Shmi let's start with you well I think there's also questions of What kinds of talent if I look at France for example I think in absolute terms the the number of kind of Tech talent in France might well be higher already I think one thing Singapore does well Andre you can comment on this is it looks at Talent holistically it's not only about the person about the machine learning engineer or the data scientist it's also about the the Singapore Academy of law for example zkin will speak later today they're talking about how lawyers can use generative AI more effectively as so I think there's a there's a whole of country approach to AI Talent it's not only about AI development Talent or data science Talent it's also about how all of all of the economy actually even students how they use AI so that's one thing I would certainly advise any country irrespective of how strong your core AI Talent is you should look at AI enabling the entire Workforce and and indeed students and heer people even that's very time intensive I imagine and very resource in intensive um Simon I I I it seems presumptuous in a way to imagine that every government of a small country might have those available resources to funnel into to AI integration you know society-wide if those resources aren't available how does a country approach this roll out yeah well again I think if you're trying to compete on scale you're going to lose to do well in AI it's well known you need talent you need data and you need compute or computational power and not everyone's going to have the computational power not everyone's going to have the data but the talent is where you might be able to make a bit of a difference and so I think the challenge particularly for developing countries is whether they want to invest in the hard W and the model development or invest in the talent that can take advantage of that and I think that goes on to shmi's point which is you don't need everyone to be a computer scientist indeed France I think is a good and bad example good example with um initiative like mistol is a great new company but um I think about 5 years ago they said right we're just going to train everyone in computer science or 20,000 computer scientists computer science is important but actually more important than just training up AI models for AI model sake is training the entire economy so that people can look out for opportunities uh because the large language models are pretty good at producing human-like text they're very good at coding so the idea that you just need coders I think misunderstands the opportunity of AI it's not just going to be a computer science regime it's going to be an economy-wide um Factor that's going to be a bit more like electricity which transforms whole economies so not everyone needs to be an electrician but you need to know how to develop tools that will use electricity or apply electricity in new ways so at what point should we be talking to children in schools about AI coding so we already are so AI Singapore there's there's uh educ there's free educational opportunities through AI Singapore for everyone I mean candidly I'm a little bit wary about getting kids too young because I think they need their screen free time but throughout the education life cycle um certainly at the University level uh we're training students to understand the opportunities and the limitations of AI not because everyone needs to be a computer scientist although we have great computer scientists but because the lawyers like Shmi said the engineers U the everyone's going to need to operate in an environment where AI is hopefully going to enhance their ability to do their job in new ways and hopefully to do new things that they never could have done in the past I've got a couple more questions and then I'm going to open it up to you in the room um Andrew you talked a bit about strategy earlier and and Singapore has remained impressively neutral um when it comes to the big AI power blocks I wonder is it realistic to think that a country of Singapore's size an equivalent country can continue in that way going forward or is that ultimately going to be a point where they have to express some sort of loyalty I think geographical diversity is absolutely critical uh as we build AI products and tools for the world uh so building on the inter disciplinary nature of AI as well as the fact that AI understanding can start from any age and anywhere um I do think that it is more powerful and more beneficial when we build AI products that are built by teams of people that are based all over the world that have specific local and Regional context that can help us to translate things uh that will suit that context better uh and that can help us to identify Safety and Security risks that may occur differently in different parts of the world too so I I think the the usual binaries or it's really an artificial construct that we have to constantly work against I'll give you a couple of examples of how sing for does this uh we obviously collaborate very closely with the US government and with us industry because they are tremendous partners for the sort ecosystem but likewise we also have conversations with the Chinese government on AI governance policies uh to build that Mutual understanding uh there's also tremendous amount of research that goes on uh at all levels um besides that uh at asan and at the un uh we are the leaders of a digital Forum of small states that's 108 small countries that are also thinking about the capacity building uh the Investments that they need in infrastructure uh the type of education and upskilling that's required for their Workforce um and we use these platforms to talk about really important subjects as to how you might want to govern AI well what sort of capacity is needed uh and how can we learn from each other uh through all of these various platforms um it's a small start and you know I but I personally think that it's a really important investment in this International collaboration uh because the more we understand what is at stake and know that we have friends and partners to to guide us through that Journey um I think we are a lot better for it it's a small start it's a mighty start um shmit so earlier this year we saw the publication of the Assan AI guide which appears notably more lenient I would say than the eu's AI act and I Wonder has Singapore had any response from EU governments has there been any push back to it I mean I'm probably not qualified to speak about what whether there's a push back or not but I think the point about lenient I mean I don't know it's there are some aspects of the eui law which appear to be restrictive to many people in the industry but I think a lot of of this debate about whether something is lenient versus something is more strict it's somewhat superficial with a small number of exceptions around the the governance of large language models and Foundation models there's actually a wide degree of agreement around the world so I would not characterize ourselves as lenient I think pragmatic would be a better word and that is true for Singapore I think that is true for asan and frankly for the whole region and you know people often for just to continue on the example I often have a lot of colleagues in the in the West in my private sector days would say well Asia can go out because um because they're very liberal and wild wild west out there in terms of actually I'm sure you know this but some of the strictest rules around Aus are actually in China which is often quoted as the wild west so I think this again not going by the binary I think Singapore's approach and indeed the Region's approach is more pragmatic rather than being and pragmatism can sometimes be very strict and sometimes it can be very liberal I think I think one of the things that Singapore is really trying to do is navigate between two sets of risks and there is a risk of underregulation if you expose your citizens to risk if the wild west comes then it can be a really dangerous environment so we've got to make sure there's a baseline of support but there's also a risk of overregulation uh particularly for a small economy like Singapore overregulation could drive Innovation elsewhere could constrain it uh and I think that's one of the things that this part of the world has really tried to to navigate between and one thing that Singapore has done and that the AI ethics framework that aan adopted also reflects is a realization that we've got to explore this new territory in partnership with industry uh and so that's why initiatives like AI verify are so important because they're not about telling companies don't do this it's about telling companies okay how can you use AI responsibly how can you live up to the standards that you all dis spouse how can we navigate this new territory together what isn't Singapore doing well that it could be doing better all of the above more more money for search sorry my colleagues at University would would me that's a c out that answer any of you any I mean okay we can frame it differently how do you hope Singapore's AI strategy to evolve in the years to come if we're having this conversation in five years time what do you think has happened by that point that we're not witnessing now so I think if I can uh respond to this what I'm seeing um and I believe these are the three sort of core pillars of uh Singapore's new AI strategy are infrastructure talent and adoption and I see these three things as being the three things that most new strategies of smaller but quite Advanced uh AI uh hubs are also focusing on so infrastructure uh I mean uh compute was mentioned earlier so a high performance compute that can sustain AI systems is really really key Canada I think secured 2.

5 billion uh dollars recently for uh high performance compute infrastructure and I think uh this will be something that we will see grow in uh Singapore as well in other countries and same for talent retention High Advanced Talent uh and Adoption of AI across different industry and different sectors India also is really really banking on this um specifically for uh sectors like uh education Healthcare Agriculture and other ones I think one thing that really will pose a challenge in the coming years and it came up in the interview with Minister too earlier is the tension between two big challenges of the 21st century which is technology and climate yeah and how we get access to the energy we're going to need in a way that still maintains Singapore's environmental commitments and I think that's going to be a really tough challenge but um it was good to see the minister and the government is very open to the the need to confront that directly um I want to open up the room to see if there are any questions if you have a question please raise your hand yes I can see one straight away at the back and someone will come to you with a mic so and if you could just stand up say name the company you're from and then ask your question that would be great thank you thanks um Ro L from PayPal um thanks um for the wonderful insights I just I was trying to tie this conversation back to the data that we were looking at prior to this I guess what I'm struggling to reconcile is I think this one fact that you shared which was that outside of the China and the US the Asia in general has 2.

6% of private investments in AI and it use private Investments as a proxy for where there's value um I. E financial gain Financial benefit and the 2. 6% fields very off fields are naturally low especially for such a large economy so I'm wondering what the insights are from the panel on what might be the cause is it that the value doesn't exist or the barriers in the foundations to getting to that value are way too high that it doesn't justify the Investments but it just feels very contuve to me so love to get your thoughts thank you who wants to take AC Sure start I feel like I should yeah you start then um thank you so much for the question so um I think actually the 2.

6 I wouldn't consider so low considering that the US makes up over 60% of global private investment in Ai and China which is also the second biggest AI player in the world makes around 9% so 2. 6% um I wouldn't consider is that low um and within it I think Singapore in 2023 was uh something like 0.

7 um billion um Singaporean dollars um which uh I feel is quite uh quite high and I think uh your point about AI private investment not being I guess the uh main metric um I think um AI government spend is also something that we look at in the index and that is very important when we look at how much um AI has been invested or how much has been invested on AI in the country um I don't know if I'm responding to this right but maybe I'll I'll I'll try and do a little bit of squaring the circle uh which is one reason you see this of course and I'm speaking now more from my previous private sector uh angle is that a lot of the investment numbers are probably more into the fundamental research and or compute side of it and not just for Singapore but a lot of Asia's approach to AI is actually about is about value where's the value now you might say well that's creates some risks in the long term if we are not the sources of fundamental research um yes but in the near term in the short term I think the cost of using Ai and adopting AI is far lower than the cost of developing brand new large language models Etc so some of that number you seeing in that the other thing I say only partly tongue and cheek is I I did work for a for a global bank with operations across from us to Asia we just get more bang for the buck in Asia that is a reality I mean we spend less um compared to some of the more expensive centers and that's not necessarily true for Singapore but certainly for the region overall you will get more value so I think the link between value and investment is probably better here if I might say so compared to yeah there there's also the question whether you rent or or Bild yes that's true um and a different kind of angle is I draw the analogy with legal services so one of the things that's been fundamental to Singapore's success is Embrace of the rule of law now Legal Services is only 0.

55% of GDP so it's a tiny sliver of GDP but it enables everything else because only with a trusted legal system that enables you to have finance a banking sector which is more like 14 15% of GDP AI is going to be the same you need core investment but to take advantage of it that doesn't require you to have all of the data centers in Singapore or indeed in Asia I would say that it's also a Time Dimension to a lot of uh this that things that we're talking about I mean you know G AI has maybe caught you know the World by by for only about 20 months um I think many Industries and businesses are seriously thinking about how to make their investment worth their time uh and as we have seen as it relates to say infrastructure sometimes it does get cheaper uh as you wait uh it's easier to buy as opposed to build um and I do think that companies and and organizations do need to think about the kind of capacity that they have within the organization and outside of it uh to make that investment worth their while um I also would would think that there is um a certain dimension of you know getting over this hype cycle and making sure that we are are building for the Long Haul which is why I think some strategic patience uh in this arena is really really critical um because you have to make these Investments not not too different from when we were doing digitalization about 10 years ago um many people thought that it would pass many people thought that you know I could sort of hold on and wait for it um but it is the businesses that um do see the value and make those Investments over time uh that will eventually see the benefits so I I would take that 2.

6% uh with a slight pinch of salt because I think that's just a snapshot of where people are at today I hope that in 5 10 years time that number will be significantly different we've got time for one more question if it's quick um anyone got a question okay yeah yes one at the back um I'm Eugene from 10 storen so I have two questions uh so firstly is many Nations right they're actually investing in r five to really it's a open source version of V so that they could really protect their supply chain uh re five when they develop re five is like an intellectual property to make their own chips uh that's number one so what's Singapore strategy around that uh and number two is I believe you know AI Compu is extremely important uh but my question is um what alternatives are Singapore looking into because it's not really good to invest all Ai and compute into a certain particular vendor uh I would say that diversity is really important for us also on this particular piece of technology um just to give some statistics uh Singapore is the I think we contribute 20% of semiconductor equipment and about 10% of global chip production um but that's not to say that we do all kinds of chips uh we are have strengthened some of them like memory for instance uh and when it comes to AI um I think while there are certain players that are dominating we know that it's still a space that uh will evolve very quickly as the technology evolves too so I would say in response um the strategy here is to make sure that you have the right trips to do the right things uh our goal is to make sure that you are um that organizations all over here uh have access to what they need um and from a government standpoint I think our investments will be you know will come across a range of options from stuff that requires to be on Prem because of our security needs but uh where there can be cost efficiencies and technological uh advantages and being a cloud will also do that too um and then going back to the question of sustainability how do we get all of this compute power for much less energy I think that again would be one metric of uh deciding Simon quick fire answer from you to end very briefly the objective for a country like Singapore can't be to be the end we're not going to be the dominant player but we want to be an indispensable partner so Singapore's history can be summed up in three sentences 19th century aort for goods 20th century aort for services 21st century aort for data and ideas so we've got to be part of that information chain that that flow which requires us to have diverse partners and uh diverse interests I think a last one for me is I think what will be key is Not Just investing in high performance compute infrastructure but also making sure that that is available to Industry and researchers to uh use and in the same way we will need uh public data set platforms with data that can be made available again for both industry and researchers to train their AI systems Serena Simon shenique and Andrea thank you so much for your time thank you