Singapore businesses are actively adopting artificial intelligence (AI), but growing data complexity and security challenges risk undermining long-term returns, according to new research from Hitachi Vantara.
The findings are drawn from a survey of over 1,200 C-level executives and senior IT leaders across 15 markets worldwide, spanning the Americas, Europe, and Asia and Oceania. There were 51 respondents in Singapore.
In Singapore, the study captured perspectives from senior business and technology leaders responsible for data infrastructure, cybersecurity, and AI strategy, providing insight into how local enterprises are navigating AI adoption, data complexity, and security risks in an increasingly digital and regulated environment.
Uneven Readiness for Long-Term ROI
The research indicates that Singapore firms are widely using AI, with nearly all (96%) local respondents reporting some level of AI use. Two-thirds say they have been successful using AI.
However, confidence drops when it comes to sustained returns. While adoption is widespread, many enterprises remain uncertain about their ability to consistently translate AI adoption into long-term business value, highlighting a growing disconnect between deployment and operational readiness.
This gap suggests that while Singapore enterprises are advancing with AI, not all are equally prepared to support it at scale over the long term.
Emerging strategic risks
As AI workloads expand, data complexity is increasingly viewed as a strategic concern rather than a purely technical one. Many Singapore enterprises report that managing sprawling data environments has become more difficult, with direct implications for governance, visibility and cyber resilience.
Among Singapore respondents, 66% say their organisation has already had success using AI, demonstrating strong early momentum.
Also, 23% rate their organisation as having strong, industry-leading readiness to achieve ROI from AI, pointing to uncertainty around sustained value creation.
In addition, 52% say the complexity of their data makes it more difficult to detect a security breach, reinforcing the link between infrastructure sprawl and cyber risk.
Further, 64% agree that if leadership fully understood how fragile their data infrastructure is, it would keep them up at night, highlighting an important knowledge between the expert executive levels
These findings indicate that even among organisations using AI, complexity and security challenges can expose underlying weaknesses in data management rather than resolve them.
Mature, risk-aware AI behaviour
As AI becomes more embedded in business operations, many Singapore enterprises are placing greater emphasis on governance, security and operational discipline, rather than focusing solely on rapid AI expansion.
This risk-aware approach reflects growing expectations around reliability and trust, particularly as AI systems begin to influence critical business decisions. However, it also raises the bar for data infrastructure, making weaknesses more visible — and more consequential — if left unaddressed.
“AI success is no longer about experimentation alone. It depends on whether data environments are resilient, governed and trusted,” said Joe Ong, VP and general manager for ASEAN at Hitachi Vantara.
“Singapore businesses are clearly ahead in adoption, but the next phase will be defined by how well they manage complexity, security and performance as AI scales,” said Ong.
Adoption and Value
The research suggests that many Singapore enterprises recognise the need for stronger data foundations but still face challenges translating that awareness into coordinated, long-term action.
While AI usage is high and early success is common, rising complexity and security risks threaten to erode confidence and returns if not addressed systematically.
As AI investment continues to accelerate, the ability to simplify data environments, strengthen governance and improve visibility will be critical in determining which organisations can move from early success to sustained value.














