For NCS, use case sharing drives faster AI deployment

“This is why use case sharing is as important because we're finding that in the industry, everyone is looking for fast but not necessary first. They don't want trial and error. They just want to go straight to something which is proven basically,” says Howie Lau, Chief Corporate Development and Synergy Officer at NCS.

NCS recently unveiled partnerships with leading global technology players as well as a S$130 million investment over the next three years to drive AI across the Asia Pacific region. The leading technology services firm also launched Sunshine AI at its NCS Impact forum in Singapore.

To understand more about the partnerships and investment, CRN Asia caught up with Howie Lau, Chief Corporate Development and Synergy Officer at NCS. Lau explained in detail how the investment will boost AI adoption in the region as well as the potential impact from the partnerships in the region.

Can you tell us more about how NCS plans to invest in AI development?

Almost every organization we talk to, whether it's governments or enterprises, talks about using AI at scale, but in a safe and trusted manner. We've been investing in AI for a while, that's why we could launch Sunshine AI.

We also felt that it's important to continue to double down and to grow investments which fall into three buckets. The first bucket is that we feel that it's important to continue innovating around tools, assets, and accelerators. We don't call it products because there's a lot of products. There's at least 10, 12 versions of LLMs that is commonly used. And there's a whole bunch of data lake solutions with a whole bunch of different platforms.

So, we're trying to help clients implement it in a more predictable, faster and safer way. We find that as we do projects and use cases, it makes sense to take some of it and make it into assets and accelerators. This will help when they actually start a project, instead of starting from ground zero.

The second bucket is because as a services company, it's all about people. And it's important for us that every person has to be levelled up. The National AI Strategy has a target of 15,000 practitioners, and we're targeting 3,000 practitioners.

Not because we want to contribute to the nation, but because we think it just makes sense because the future work is going to be AI. And for us to deliver a good job, we need all our people to be conversant. A simple analogy is that for every member of staff, we potentially have three agents working with us and working for us so that our productivity grows. So that is a combination of the proprietary set of tools and capability.

Then the third bucket is continued partnerships to go and do experiments and innovation. This space moves so fast, and there is a continued need for experimentation.

So, the S$130 million kind of goes into these three buckets. The proprietary tools, accelerators and assets, the continued up-levelling of competencies, and then the continued experimentation.

Will this be a regional focus?

Yes, this it for the region because we're finding that the learning and the tools are best built on a regional level.

For example, the use case deployed by Singapore’s Ministry of Manpower is also being deployed in Australia. Because a lot of clients see it and realize they would like a similar use case because they can see productivity gain. They also see the thinking around risk mitigation to implement.

This is why use case sharing is as important because we're finding that in the industry, everyone is looking for fast but not necessary first. They don't want trial and error. They just want to go straight to something which is proven basically.

We see wonderful innovation in Australia, China, Hong Kong and Singapore. We work with partners across the region.

Also, when it comes to capability, not all countries have it. But when we look at it collectively and if you balance your capacity, potentially you have more than you think because of the ecosystem.

Is this where partnerships play an important role in the NCS ecosystem?

As a systems integrator, we're quite fortunate to work with many different partners. And because of that, we kind of see the strengths and capabilities of our partner. And each of these partnerships is timely because they are all geared towards creating some level of solutions together that doesn't start from ground zero or competency and capability development.

With NVIDIA, we've been a long partner with them for a while. NVIDIA does more than GPUs. They have their own solution and their software framework. With their solution framework, we can work with it and take some of their best practices and their frameworks to actually build agentic AI solutions that we can then bring to our client, so that we can fit into the end-to-end story. They are more known for hardware, but their software stack is actually impressive.

Sunline is the largest core banking solution. We kind of like it because firstly, the feature functions of this core banking solution are really infused with a lot of AI elements into it. More importantly, there is a wave of upcoming core banking refresh. We felt that there's a match in terms of their capability and the clients that we have.

In a way, it also kind of demonstrates that we're quite unique in that we have the opportunity to work across Western-stack companies and Chinese-stack companies. Whatever makes sense for the client, we're a little more flexible to work across.

Interestingly, for the partnership with Databricks, it's the first in Southeast Asia. We actually have partnered Databricks with NCS Australia. Then, it dawned upon us that we have Databricks engineers for doing projects across different, but on an aggregate, we're actually a pretty big Databricks practitioner. Same logic in that many clients are saying, I don't want to start from zero, so we took the projects. You leverage what you have there.

With regards to the Western and Chinese tech stacks, how do you foresee this scenario panning out, especially with the uncertainties around tariffs?

We will have the second order of impact because when it impacts the clients, obviously it impacts us. So, on the first order of impact, it's all the tariff side hardware.

But the second order of impact has both sides of the coin. The negative side, obviously, is that if a client is now impacted negatively, their cost pressures will be higher. Then there might be reductions in spending.

The positive side could be that because of this, the need to reconfigure their supply chain will require a relook in terms of the design of the supply chain and the implementation of the supply chain. So that could lead to spending. However, we don't know. We haven't seen it yet because no one's reacting because it's so uncertain.

That's the scary thing. I cannot plan because it's uncertain. I know I should do something, but I can't because it's uncertain. And if you do something, now you might change again after that. Science and AI, investment, all that. It means the rest of the year, no more nonsense.

So how does the future look like for NCS?

Now, NCS is only very focused on three key markets - Singapore, Australia and Greater China. We see growth potential in all three markets, partly because we're still growing. But there's no one market or group that can sweep it all, because it also varies by industry. And then even within industry, there are different customers with different maturity levels, because there will be some that are thinking about, the more mature ones with multi-cloud infrastructure and all.

I think the aspiration for us is that we would like to be a partner for a client who is doing their AI transformation. That they can look to us and say, “hey look, you're someone that can help me work through the different technologies required to give me the right balance of AI-led innovation with strong digital resilience and also someone that will be around for a good many years that I know I can rely on you to keep running with me.”

We know that this AI play is not fair. It's not short-term. It will continue to evolve. We will still have to figure out on a long-term basis how do we continue to gain the trust of our clients to say, “we will still be there on the next iteration of AI or whatever else comes along, to be there to help figure out how best to translate technology into helping them with their business needs.”