Speeches
Opening Remarks by Minister Josephine Teo at Workato's launch of AI Lab
7 November 2025
Amlan, June, Ee Shan,
Colleagues and friends,
Good afternoon, and thank you for having me. I am very pleased to join Workato as you launch your first AI lab outside of the US. As your company continues to grow and expand, I am sure you will continue to explore other areas and opportunities.
We feel very privileged to be the first of, perhaps, what's more to come. As we approach the end of the year, it's a good time for reflection. If we were to look back at all that has happened in AI development for Singapore, I would say that 2025 has been a good year. All the activity drivers that we had identified as part of our National AI Strategy – in government, research community and industry – have seen encouraging progress.
In particular, I just want to call out the fact that across all industries, Singapore now has over 50 AI centres of excellence. They don't necessarily only serve their teams in Singapore but also have a global mandate. From the time that we were just toying with this idea, to the fact that we now have over 50 – I think it is a big leap. It just gives us the motivation to try and get more.
As part of the idea of getting more, we did launch an Enterprise Compute Initiative. The reason is very simple – we do not assume that everyone has got good access to compute. If you are a big company, perhaps you know that is a given. But if you are a smaller enterprise, even if you had a very good idea, compute may well turn out to be a showstopper. We didn't want it to be so.
As a result, through partnerships with Google Cloud and Microsoft, we worked out the scheme that will enable more companies with AI ambitions to get cloud credits as well as AI tools and, most importantly, consultancy.
How do you get it all to work? I should also say that with all of these activities pushing ahead, we wanted to make sure that we continue to build capabilities in AI governance. I will say a little bit more about why it's so important to us.
Some of you may be aware of past efforts that we put in to build up AI Verify, this is a testing framework and software toolkit. On top of that, we are also looking at the South Shore. So, we built Litmus and Sentinel. To be able to identify what's wrong with an AI model, you need to be able to fix it too. That's why Litmus and Sentinel come as a pair.
We have also looked into areas, such as what happens when you use personal data in AI, and we have some guidelines on that too. This year, we launched a Global AI Assurance Pilot focusing on the testing of Gen AI applications in the real-world context.
More recently, on the sidelines of the Singapore International Cyber Week, we decided to launch a set of guidelines on securing authentic AI systems. The reasons are very simple. We want to try and get ahead of the rapid deployment of agents. All of these efforts really reflect our commitment to being a hub for responsible AI.
The reasons why we believe this to be important are twofold:
Firstly, citizens need to be able to trust that the AI that is being developed and deployed in Singapore is safe to use.
Secondly, is that global AI assurance standards haven't been stood up.
In the process of developing these standards, Singapore would like to have a seat at the table and help shape these global norms. So those are our objectives and we continue to focus on responsible AI.
With all of these happening, we also want to reflect on what more is needed. And I think it's fair to say that we see opportunities for the AI ecosystem to better support enterprise as well as workforce adoption, where enterprise adoption is concerned. If you read some reports, you may be feeling a sense of euphoria and over-confidence, and we don't want to do that.
If you look at Microsoft's recent report on AI diffusion, they had put Singapore as among the top countries. We always tell ourselves – that's what they say, but it's not where we want to be. Our own recent study within the industry does give us a sense that there is progress.
For example, adoption seems to have expanded in 2024 – it was about half of the companies that we surveyed. This year, it has gone up to seven in 10. I want to qualify by saying that, when they say they're adopting, it may be quite basic workplace productivity types of adoption. We don't want to kid ourselves into thinking that the number should fuel you or make you feel very comforted.
The other thing that came out through the survey that is useful, are the challenges that companies identified as reasons why they have not gone further with AI adoption. Amongst the most commonly-cited challenge is identifying practical business use cases. 54% of the respondents said so, and 49% cited the lack of funds.
48% of respondents talked about a very practical issue – uncertainties, in terms of the return of investment for the use of AI. So, if there is no ROI, why incur the cost?
Workers also are using AI to a larger extent. Today, 78% of them say they use AI in one way or another. This would be about a 9% increase from the last year.
However, if we look at the non-users, it's also quite telling. They say that a limited access to AI tools has not made it easy for them. 50% of them said so. About 28% of respondents say that they lack the knowledge on how to use AI tools.
Whether it is in terms of enterprise adoption or workforce adoption, we see progress. However, we also see gaps that ought to be plugged. Whether we look at the glass as half full or half empty, there is more to be done. Thus, we are actively growing the pool of AI practitioners through programs like IMDA’s Tech Skills Accelerator programme, and others at the sectoral level.
Another very important thing that we have learned through setting up the AI Centres of Excellence, is that your AI practitioners – who are your data scientist and machine learning engineers – cannot work in isolation. They need to work with domain and functional experts – people who know the production line and how the function is supposed to be carried out. We are also encouraging non-tech workers to be more AI-fluent and to use AI as a teammate – not to replace themselves, but to help themselves work even more effectively.
Let me just come to the last part of my comments, which is how Workato and the AI Lab fits in. I see many areas of overlap, where we share a common interest. We see you as a very important part of our ecosystem, in building up responsible enterprise AI adoption.
We know that you're working on custom agents, and we know that that is precisely what is needed in many instances to be able to address specific use cases, not generalised tools. You need to have things that are bespoke that works to your context. Apart from reducing time for value work and improving accuracy, the potential cost savings would translate into clearer returns on investment. The ROI is exactly what businesses want to see.
I know that apart from custom agents, you're also thinking of collaborative agents, and this is pushing the boundaries.
I would also just like to call out that Workato sees the need to strengthen AI governance too, and so the lab plans to develop new test frameworks. What will they do? They will evaluate the agent performance in practical scenarios.
I believe that you are not only looking for agents being able to do good work. I am quite sure that you also want to assure your clients that the agents aren't going to be up to no good – that the risk of them going rogue is not going to be present, or maybe the risk is reduced to the minimum. In this work, I would encourage you to engage with GovTech.
GovTech is also experimenting with the use of agents. This year, we introduced an agentic risk and capability framework. The reason behind this was because we want to understand the risk before actually delegating autonomy to AI systems. Our purpose as a government is not just to use it to deliver public services better, but also to be able to share lessons with Singapore's broader community of AI practitioners.
On that note, I would like to say that we welcome the addition of Workato to the AI ecosystem in Singapore. We are very happy to know of the partnership that you have with the six Institutes of Higher Learning, because we, like you, recognise the importance of continuing to invest in growing the talent pipeline.
I hope that there will also be opportunities to upskill the broader Singapore workforce. This could be done, for example, if you bundle training with deployment to enterprises, and offer insights through the SkillsFuture supported programs where the opportunity presents itself.
Once again, congratulations to the whole Workato team, and we look forward to continuing to work with you.
Thank you so much.