Opening Address by SMS Tan Kiat How at A5X

Mr Heng Swee Keat, Chairman, National Research Foundation

Professor Tan Eng Chye, President of NUS,

Friends from NUS

Excellencies and members of the diplomatic corps

Start-up founders, colleagues and friends

1. Good morning.

2. I would like to thank Professor Tan for the thoughtful reflection on entrepreneurship. Congratulations to NUS Enterprise on your 25^th anniversary. I was fortunate to be around when it was first formed. I have seen very exciting and impactful projects coming from NUS Enterprise. I am sure the next 25 years will be equally, if not, more exciting!  

3. Professor Tan reminded us of the building blocks for innovation coming together — talent meeting opportunity, research meeting real-world needs, capital meeting conviction, and local ideas finding their way to global markets.

4. I think that is exactly the right place to start when we think about Singapore’s next phase.

5. AI is changing not just technology, but the economics of innovation. Intelligence is becoming more capable, more accessible and more abundant.

6. So what becomes scarce, and therefore valuable?

7. Increasingly, it is not intelligence itself. It is the things around it: judgement and domain expertise, trusted data, talented people, real customers, capital, and importantly, the ability to bring all these together.

8. For Singapore, that is important. We cannot compete with the largest economies on scale. Our opportunity is to become exceptionally good at connecting these strengths and turning new ideas into real-world impact.

9. That means shortening the journey from discovery to application, from application to enterprise, and from enterprise to global scale.

10. Singapore has invested steadily in research, universities and talent. But excellent research does not automatically become economic or social value.

11. Universities therefore have a role beyond teaching and research. They can bring researchers together with entrepreneurs, engineers with domain experts, and ideas with real-world problems.

12. A great university should not only produce knowledge. It should help knowledge travel, from the lab into products, from products into enterprises, and from enterprises into society.

13. AI can speed up parts of this journey, from discovery and prototyping to testing and product development. But translating research into adoption and real use requires many of you in the room – entrepreneurs, engineers, capital, customers and, from the government’s point of view, effective and sensible regulation.

14. This is where NUS Enterprise’s AI Accelerate Programme and innovation sprints are useful: bringing all these together around   practical problems.

15. But getting a promising technology to work is only the beginning. It needs a team, product and engineering capability, and many of the ingredients we spoke about.

16. One of the most valuable things an innovation ecosystem is the first serious customer. A committed early customer can be transformative. By testing the solution against real operating needs, the customer helps expose weaknesses, sharpen the product positioning and build evidence that gives subsequent customers confidence.

17. So a strong ecosystem is not simply one with more start-ups. It is one where start-ups are connected to the real economy. I'm very glad to hear from Professor Tan that tomorrow we will see the first defence hackathon. I must say that our defence industry and defence agencies are very demanding, serious customers. But that's where the rubber hits the road, where founders can work with established companies, researchers with users, and investors can see a credible path from technology to market.

18. No one institution can take an idea all the way from research to market. The connections between institutions make the journey possible.

19. And then comes scale. Singapore is a good place to start, but for many companies it cannot be the final market.

20. So we should ask not only, “Can this work in Singapore?”, but also ask, “Can this travel beyond Singapore?”, “Can it adapt to different markets?”, and “Can it reach customers across Asia and beyond?”

21. Our small market in Singapore has always required us to think beyond our shores. In the age of AI, we can turn that into an advantage: use Singapore as a place to build, test, learn and gain reference customers, and then scale beyond Singapore’s market.

22. Singapore should aim to be a place where we are good at converting ideas into products, and products into real-life deployments; where innovations prove themselves, and a launchpad from which they can scale.

23. AI also changes how we think about where to focus. As the cost of producing intelligence falls, some complements become more important, as I mentioned earlier, the systems around intelligence. 

24. I always use this analogy – if you give two enterprises the same AI model, would they produce the same results? Certainly not. One enterprise may use it for AI assistance for their employees – faster emails, faster summaries, maybe even deploying agents so they can respond automatically when their bosses email them. But it is still the same organisation, perhaps doing the same work a little bit faster. Another organisation uses AI in a much more effective, deeper, and transformative way – changing the way they do things, the way they serve clients, connecting AI with their data, rewiring organisational culture, changing the workflows and processes, and creating new business model and services. I use this to illustrate my point that it is the system around AI, and the technology that will be the next important race.

25. The current race in AI that we think about is: who has the most compute, and who has the most frontier AI models. But the next race is equally important: it is building the systems around AI – not only within enterprises, but across entire industries.

26. I also wear another hat at the Ministry of Health. When I travel around the world and look at our healthcare system, I see that the same system and technology does not produce the same results. In my mind, the equation is: “health impact” equals “AI times health-system capability”. Even with the most capable AI, if the healthcare system cannot absorb, adapt and use it effectively, it will produce very little marginal effective gains.

27. The same thought experiment can be extended to the wider economy in Singapore. We want to produce and develop an ecosystem around technology and ideas, allowing it to flourish, as Professor Tan earlier mentioned. Singapore's role and positioning in an AI race is not the same race as everyone is talking about now – frontier models, compute, capacity and AI capability. But another race – creating the system around AI that allows ideas to flourish, and maximise impact in the next AI race.

28. I see similar opportunities in many areas besides healthcare, which I mentioned earlier. In Singapore, we have set up a National AI Council, chaired by the Prime Minister himself, to identify national AI missions that focus on real world impact using AI technologies and building the ecosystem around those domains. Healthcare is one of them, as I mentioned earlier, as well as finance, advanced manufacturing, and connectivity. A competitive advantage around building that system compounds as you continue to learn, adapt, deploy, and scale. I invite all of you to be part of this new AI race that Singapore wants to be in.

29. In China, they always use this term 赛道 (racetrack). I don't see AI as a World Cup, where there could only be one champion.  AI is more like the Olympics – there are many sports and Singapore has to decide which sport we want to be in to give us the best chance of getting gold medals.

30. I bring this back to why A5X matters. Its value will not ultimately be measured by the number of people in this room. It will be measured by what happens because, as the theme of A5X suggests, the next decade is in this room. (Note: The theme of the event is “The next decade, all in one room.”

31. It is also because of the connections you make, the people you meet here – that is how connections become capability, and capability becomes impact.

32. In conclusion, Singapore has spent decades building many of the ingredients of a strong innovation economy – research, talent, entrepreneurs, capital, infrastructure, trusted institutions global connections, and top-class universities.

33. The next phase is about making these pieces work together even better – more discoveries becoming applications, more applications becoming enterprises, and more enterprises reaching the world.

34. AI will change what is possible, but technology alone will not determine what we achieve with it.

35. For Singapore, remaining relevant in the age of AI will depend on how well we connect the people, institutions and capabilities around innovation, and how quickly we can turn new ideas into something useful and scalable.

36. As intelligence becomes more abundant, our advantage will increasingly come from our ability to connect, apply and scale it. Building a system around AI allows technology to create economic and societal impact. 

37. Thank you very much, and I look forward to witnessing the next phase of NUS Enterprise.