- FSI’s in Malaysia are still spending strongly on upgrading technology with AI a key component
- Malaysia needs to invest in developing higher quality AI and cloud engineers to really capture global opportunities
Talk about living with pressure. “We have a 20% growth target this year,” said Henrick Choo, Managing Director of NTT Data Malaysia Sdn Bhd. And before this writer could ask a follow-up question, Henrick, anticipating it, dead panned, “My head will roll if we cannot hit it.”
Fortunately for Henrick, whose jovial nature has endeared him to colleagues, customers and competitors alike over a three plus decades tech career, Japanese tech companies are not ruthless like their American rivals. And Henry has kept his head despite missing an even higher 30% growth target for 2025.
“Our revenue base is quite large, so it is hard to hit such targets,” he explained. “Even hitting 10% to 12% growth is good,” he said, declining to share the precise growth rate hit in 2025 or how much its yearly revenue is.
Still, the 20% target for this year says something about what Henrick is seeing on the ground. Malaysian enterprises are still spending on technology. But they are not spending as aggressively as large companies in Singapore, where his NTT Data peer is seeing customers move fast and earlier on, AI especially. “We are always a bit behind Singapore, which is very advanced. I think the government is giving a lot of incentives for people to invest in AI in Singapore. Their companies are at least two years ahead (of Malaysian based ones),” he opined.
Irrespective of the pace and aggressiveness in making tech investments by corporates in both markets, the crux is about survival, Henrick believes, making a stark point that is not atypical of enterprise tech leaders, who, if one chooses to be cynical, are measured only by how they can grow sales.
Still as one of the most senior and respected enterprise tech leaders in Malaysia, he became head of NTT Malaysia in 2019 following the combination of NTT Communications, Dimension Data, Emerio, NTT Security, and other entities under the NTT Ltd brand, Henrick’s decades of experience in the Malaysian corporate tech landscape does lend weight to his views.
Speaking specifically on investments made by customers around AI, he notes, “Maybe you don’t get an outcome from the investment, but if you didn’t spend on the project and your competitors did spend on AI, and benefited, and are able to out-compete you, your company may just collapse.”
Dramatic for sure, with his blunt assessment being: “The risk of not spending is higher than the risk of spending.”
He elaborates: “If you spend wrongly, you may burn the money, but your risk of not spending is that one day your competitor can do something extraordinary.” Trying to react means one is at least 18 months behind.
Interestingly, it is not just the corporate customers of tech vendors who are facing this risk of being left behind. Even the tech vendors are. Witness the statements by Oracle Corporation when announcing 21,000 job cuts recently and attributing this to AI’s impact. “If our competitors’ AI products achieve higher market acceptance than ours, we may fail to recoup our investments,” Oracle said, adding that if it doesn’t continue to invest aggressively into AI, it might fall behind the curve.
Still, the key point Henrick wants Malaysian boards to grasp is this. “Imagine a company using AI agents to reply to customers and handle collection and everything as well. If your competitors reduce their headcount by 40% to 50% by doing this, meaning their cost of serving the customer is a fraction of yours, then suddenly you have a different cost structure compared to your competitor.” Scary, right? Very scary,” he says.
Where Malaysia is spending
Back home, Choo does not see technology budgets collapsing. “I cannot see any warning signs now,” he says, though he cautions that macro risks can travel quickly. “If the bank customer is not making interest payments and has cash flow problems, the bank will get cautious and maybe cut its spending. It’s a whole chain.”
For now, financial services remain the anchor for NTT Data. “60-plus percent of our customer base is FSI and it is doing well generally. Whether insurance or banking, they are all doing well,” he says.
Conversely, doing well also means drowning in transformation work. “There are a lot of transformation initiatives going on in the FSI space. There is almost too much transformation. They cannot cope, actually. But this sector will continue to spend big time,” he confidently predicts.
The transformation work going on is not just of safe, small scale pilots that harp big on innovation. “They are replacing some core banking systems. Some want to regionalise all their applications, for example using one single credit card system. Those are very massive projects,” he says.
Henrick notes that some large Malaysian enterprises have moved beyond basic awareness of AI. “Every customer has their data and AI teams with one bank having between 60 to 80 people. They are already very knowledgeable,” he said mentioning two regional Malaysian banks in particular but requesting their names not be reported.
Despite the various ongoing projects, the gap lays in production impact. “To put their AI pilots and POCs into production use, we haven’t seen the real impact yet. But we think that’s coming,” he said, confident.
Much of the current investment is going into the unglamorous work that makes AI useful. “Customers are now focusing on their data, preparing their data. Malaysian banks’ data systems are already 30 years old, at least, because all the banks started their data warehouse systems in the 90s.”
The result: “Banks are now building new AI-ready data systems. They are preparing for it, building the structure, data governance, data framework. Last year, we had at least three projects worth more than RM20 million each. It’s all related, getting AI-ready stage by stage.”
Cloud, cost, and control
While there has been a lot of pushback in recent years against the high cost of cloud adoption, which some critics contend has been a big lie by big tech about the oft promised lower cost of the model, Henrick argues that it is not the problem people assume. “In Malaysia, cloud adoption is not that bad,” he says. “We have projects helping clients move to the cloud, building their data structures, building their CRM.”
For banks, the cloud model is hybrid. “Mostly hybrid, because their core banking system is on-prem, except for digital banks which are full cloud. For the traditional banks, some front-end applications, AI applications, rapid development applications, actually only make sense on the cloud. It changes so fast. But traditional SAP, stable applications, month-end batch, day-to-day operations, many of them will probably remain on-premise because cloud cost is also not cheap.” The cloud is good, he stresses but acknowledges that it is not cheap.
Ironically, the economics of on-premise are now helping cloud. “CPU shortage, memory shortage. VMware is three to four times the price already. Server and storage prices have doubled,” he says. “I had to order over 100 laptops for a managed services project we recently won, and the price per laptop had increased by RM1,000.”
Talent decides the upside
For Malaysia to become more than an overflow data centre destination, Henrick is clear on the bottleneck. “We have power. We have connectivity. But the gap is in the skills, especially the higher level skills, to exploit these technologies and then export our services.”
NTT Data is already pushing Malaysia as an APAC delivery centre, anchored in Cyberjaya. “The good news is that we are not just delivering services domestically, but that we are exporting them too,” he says.
Still, the skills gap is real. “We need to build highly skilled talent around AI and cloud technologies. We do not have enough very highly skilled talent here, especially coders and application development. To the extent that I need to bring in engineers from India.”
Unknown to many, since its earliest days in Cyberjaya, where NTT’s data centre there was its first ever outside of Japan, it has cultivated a close relationship with Multimedia University (MMU), sponsoring two professors for a number of years and sponsoring students on full scholarships as well and hiring a handful of them on a yearly basis.
“This began in the early days of the Multimedia Super Corridor vision in the late 1990s. Till today, we are doing our part to develop and uplift Malaysian tech talent.”
Coming back to the tech spending by enterprises, Henrick reiterates that Malaysian enterprises are spending, especially in FSI, with the serious money going into building a strong foundation for the AI economy: data, governance, cloud, core systems, and talent. And he cautions that, when it comes to AI, any board decisions to delay investing is no longer about prudence. It can become a cost structure they cannot escape.
The first draft of this article was produced by AI with the writer working on the published version.
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