楊莉明部長在《AI 在東南亞：機遇時代》報告發佈會爐邊對話實錄

Moderator Daniel Pacthod, Senior Partner, and Chair, Leadership Initiative, New York, McKinsey: It's a privilege to see you again. We were together on a cold mountain a few weeks ago in Davos. I'll start with this – I think we heard a lot in the introduction about Singapore and ASEAN as a gateway and hub for AI. When we were in Davos, there were actually a lot of discussions from a lot of players, from the tech and the AI ecosystem, about investing in Asia, in Singapore. Love to hear from your perspective, what makes Asia and Singapore a good place to invest when it comes to AI and the future of agentic and some of the key tech moves in the ecosystem?

Minister Josephine Teo: Well, the landscape is very wide , and when companies look at what they would like to devote their time and attention to doing, it also depends on what their starting points are. If we just look at companies that we could describe as being at the frontier, when you are a frontier company and you're thinking about how best you deploy your resources, the idea that in Southeast Asia is a market, and this market is receptive, and at some point in time, this same market is interested to invest, and is interested to try new things. I think that is attractive. Ih-Ming already spoke about that. The report also covers them quite extensively.

But when they go to the second level of decision making, the conditions that they are looking for, throws a bigger challenge at them. It's one thing to find a location where they can access compute and have basic infrastructure that they don't have to worry about. It's quite another thing whether they can access a pool of talent. When companies relocate from one place to another or start up a new place, your first series of actions almost always involves poaching, right? So you must have a rich environment and a rich ecosystem from which to poach to get started. It's not necessarily a bad thing. It creates dynamism and urgency in the market.

But if this talent ecosystem isn't expanding, then we're just poaching from one another; it doesn't grow. So it has to be a talent environment that is also organically growing because people are attracted. And why are they attracted? Maybe it's because the living environment is good. But I think when it comes to AI, talent is sought after everywhere in the world. Their interest is in plugging into networks where there are like-minded talent, people who are engaged in solving interesting challenges, people who bring something to the table. They have a new insight, they read a paper, they came across another AI researcher, or they came across someone with domain expertise, and they are trying out a very interesting idea, and you need to have that buzz to plug into. That's a very important consideration.

For a company at the frontier of AI, probably the single most important factor that they consider is who can grow together with them, because they are devoting all of their precious time and resources to try and identify a worthy use case. The organisation that owns the use case must not only have the resources; they must have the ambition, they must dream big, they must have the wherewithal to grow along with them. And if they can only pick a few partners to grow together with, where can they find them? And the reason why this is so important is because, when you are at the frontier, it's so competitive. What you lose is time and opportunity, if you invest with the wrong partner. So I think this is what makes Singapore interesting. Here you will walk into a healthy ecosystem. I think the bench strength is here. But what I also see is that there is a growing appetite for risk-taking. There is a certain amount of dare. There is imagination. When I spoke with leaders of frontier AI companies, that is what is drawing them, that's what they're thinking about. When they look at the landscape, they say: “Here is an interesting market. How do we find ourselves a gateway? How do we find ourselves a foothold?”

I think there is just one other thing I would add. These individuals, these organisations, when they are doing their calculations , they also look at where you are putting resources. It's not helpful if you are putting in resources into building data centres - hat's really hygiene, that's very baseline. They are looking at whether you're putting resources into research and development (R&D), whether you are investing in science? If you are doing those things, then perhaps they see that there is a greater headroom for them to bring the best that they can contribute.

I will say that these are the factors that help frontier AI companies think about Singapore when they try to choose a location to access the Southeast Asian market, as well as, of course, the broader Asian market.

Moderator: Thank you, Minister. From Davos, and even in the last few months – the two words that come up a lot are speed and trust. This is a technology that moves a lot faster than regulation. What role can Singapore play for a more responsible experimentation, and also for unlocking speed? Because to some extent, some people are a bit constrained, and there might be fear in the system or too much risk, but what role could Singapore play, where people could actually lean forward and roll faster while maintaining the trust with the technology?

Minister: Daniel, I guess when you think about speed, you're thinking about how quickly we can scale the adoption to the wider economy so that it doesn't stay only within frontier companies? You want to find a way for it to diffuse.

I think, at the individual level, and the numbers bear this out – many of us have experienced what I could refer to as an IKEA moment. An IKEA moment in the sense that when you use ChatGPT, you realise that it's not that difficult to use. When you experiment with NotebookLM, you realise that you can create a podcast too. It's not that difficult. If you use Nano Banana, you can create all these fancy things, right? And that is the IKEA moment for us at the individual level. But if you unpack it a little bit, how does this IKEA moment come about?

This IKEA moment comes about using IKEA as an example. The first time you step into IKEA – you've never assembled anything on your own. If you see that there are many people seemingly very confident about buying stuff that they can bring home and then build – maybe you think: “It can't be all that bad, let me try it too”. When you bring it home and unpack the package, what actually helps you get the job done? There have to be some simple instructions. The way the object, the product, is designed, is relatively easy for you to assemble. Maybe the first time you build a bookcase or a simple table – the legs don't exactly balance, and it's not perfect. But you gain some confidence. And the next time you buy an object, you assemble it, it is slightly better. You pay more attention to the instructions given to you. The IKEA moment for individuals came about with people using ChatGPT – it's not that difficult to use. The IKEA moment for enterprises – that's still not widespread enough.

We have over 60 AI Centres of Excellence built up already. When we first started, we thought, “Who would be so brave as to think that they could get this off the ground in Singapore?” And then we saw something interesting happen. The first 10 were not easy. The next 10 were a little bit easier. By the time we got to 30, the team was updating me at such a fast clip that I was pleasantly surprised. And it seems to me that at least among some of the leading companies in Singapore, the IKEA moment has arrived.

But we are not satisfied with 60 or 100 AI Centres of Excellence. This is a democratising technology. Rightfully, it should reach thousands and tens of thousands, and that's something we should work towards now. So, to your question, how do you get to this kind of scale, and how does experimentation come about? It's not going to be the individual buyer of IKEA products who does the testing. You buy it, knowing that it was built with a certain degree of reliability. In the early days, they made a great effort to show you how many times the sofa was jumped on, how much the desk can withstand, or kids playing on it.

The same concept applies when we invest in building up our testing capabilities, when we develop our governance frameworks. These are not necessarily intended for the end user of AI to satisfy themselves with. It's going to be the aggregators. It's going to be the equivalent of IKEA that has to invest in this effort so that when they distribute AI tools, they come with a certain assurance, seal, and certification of reliability. That is the journey that we are going through right now. And I'm reasonably encouraged by the response. Certainly, I think within the ecosystem in Singapore, there is a good understanding that if you want this technology to go further faster, you need to assure the people who are using it that it is safe. You have heard this many times before – you can drive faster only because you know that there are seat belts and airbags. You just have to develop these systems. So, this responsible experimentation – we have to think about where it needs to happen. It's not going to be at the individual level or enterprise level; very often it has to be at the level of the aggregator that gets this done.

Moderator: Minister, perhaps going back a bit to the report. As we put the report together, we're honourably excited and passionate about the future of Asia and Singapore in this AI revolution. One of the things we picked up as we worked with the private sector last year was all about use cases. This year, it's all about what's the reimagined moment? And how can you reimagine your company, your country, agentic first? I know you have always bold ambitions. If you were to go out two or four years and think about what you would have achieved, what are some of the markers for Singapore in terms of leading the way? What's that reimagined marker for Singapore in this AI revolution?

Minister: I think it has to be in the people that you speak with, how they're describing their work today, compared to four years down the road. It has to be in the business owners and how they're describing to you their next big idea, how they're going to grow their market, and how they're finding new and in interesting ways. And I think when you speak with individuals, enterprises, and government officials, you see that there is a change in the way they think about their work.

The day before yesterday, our Government Technology Agency moved to a new premise in the Punggol Digital District, and they had a little opening for their staff, so I was there. And our team that is helping the whole of the public sector to think about the use of AI, told me that the platform that they built, which is a platform that enables public officers to build AI bots for themselves. So, for example, Daniel, you are a colleague who is so inquisitive, you're always asking me questions, and in answering all your questions, I have no time to do my own work. Imagine if I have 10 colleagues like you constantly doing that. What if I build a bot to answer your questions? That's exactly what many officers have done. We have over 1,000 bots built by public officers. Are all of them fantastic bots? Of course not, but a good number of them are actually pretty good.

And this is the kind of momentum that we like to see - the enthusiasm, the ‘Aha!’ moment that has reached the individual. The ‘Aha!’ moment has reached what they can do in the workplace. It needs to reach the whole organisation, and bring about excitement across different industries.

Moderator: We had one question that we also sourced from the audience. You talked about talent in your first remarks. When we work with clients, it's very clear that any AI transformation is actually not technology, it's actually people transformation. You had a lot of ideas on, how do you make Singapore a bit of a hub for AI-enabled workforce? Say a bit more about the vision you have on how you actually solve the talent side of AI and make Singapore as an AI hub.

Minister: In just the two years since we refreshed our National AI Strategy, I think our thinking has also shifted. The way we look at talent has also shifted. At that point, we thought of talent in three tiers. We were thinking of AI creators – people who design the most sophisticated models and put out AI tools that the world wants to use. Then we were thinking of AI practitioners – these are basically data scientists and machine learning engineers, who then bring these ideas back into their specific context to make sure that there is an actual useful application. But we also thought that if you didn't have the broad base of AI users, it couldn't support AI innovation in a very significant way. So, a very simplified way of thinking about creators, AI practitioners and AI users. I think our perspectives have evolved. The AI talent ecosystem is much richer than that.

The best example I can give you is perhaps when you think about our airport, you think about how you get the terminal going. Somebody has to design the terminal. Somebody has to get it built, make sure that there are systems and processes to maintain it on a regular basis, and think about the most useful technologies to apply to make this terminal work. Then comes along somebody else who says: “Ah, you have this new, exciting, great idea, right?” Then they have to also assemble a cast of talents. But if you ask yourselves, even just Changi Airport, T1, T2, T3, T4, and in the future T5 – what makes this airport so outstandingly great? Of course, each terminal has to be great, but you don't, as a user, as a traveller, stick with one terminal. It depends on how the airlines are routed, and it depends on how we optimise the slots available to us. So when you think about building a new terminal at T5, on a standalone basis, it is outstanding. But its real value is unleashed when it's able to connect back to the existing cluster of terminals. And that is really difficult, because you have to think in terms of how do you move from this terminal to the other terminals? Even if they move the people, how you move the vehicles that move them? And, very importantly, how do you move the packages? So that requires a whole new way of thinking. That’s just the hardware, the infrastructure, the logistics of getting things moving around. You don't just want a shell where people travel in and out of. You want it to be an experience. Then you think about the other terminals being very green. Can we bring the same type of greenery? And then you ask yourself, what makes it possible for you to deliver that? Well, we need horticultural experts. I don't know how many airports hire horticultural experts, but Changi Airport does.

Now if you extrapolate this and think about what AI could potentially do for us – AI transforming manufacturing, AI transforming healthcare, AI transforming banking. The real value is not just that they are individually transformed as industries, as enterprises within the industries. It's when you add them all up and they interact with one another in new ways that were not possible before, and also more impactful than we hope. So, when we think about talent, the need, the ambition, also has to grow. You can't just think about them in a very narrow way. You have to think about a whole ecosystem coming together with talents in every nook and cranny, at every level. That's what I think will give us the most returns.

I don't want to give too much away, and in any case, we have run out of time. As it turns out, in less than 30 hours, the Prime Minister, who is also Finance Minister, will deliver the budget statement, and he will have more to say about it. But what he will say reflects this sort of maturing of our thinking about what it takes to make this technology really come alive and enable this democratising general purpose technology to really give us an uplift that we have not even imagined the full extent of.