Singapore firms accelerate AI adoption but data and security gaps threaten long-term returns

Singapore enterprises are moving quickly to adopt artificial intelligence, but rising data complexity and security weaknesses are emerging as major obstacles to sustaining long-term value. New research from Hitachi Vantara suggests that while AI use is now widespread across local organisations, confidence in achieving consistent returns on investment remains limited.

The findings come from the Hitachi Vantara State of Data Infrastructure 2025 Report, a global study examining how enterprises are preparing their data infrastructure to support AI at scale. The research surveyed more than 1,200 C-level executives and senior IT leaders across 15 markets in the Americas, Europe, and Asia and Oceania. Within the Asia and Oceania region, responses were gathered from 425 leaders, including 51 respondents based in Singapore, covering a broad mix of industries and organisation sizes.

In Singapore, the survey focused on senior business and technology leaders responsible for data infrastructure, cybersecurity, and AI strategy. Their responses provide a snapshot of how local firms are balancing rapid AI adoption with the operational realities of managing increasingly complex and distributed data environments in a tightly regulated market.

Strong AI momentum meets uneven readiness for ROI

The study shows that AI adoption in Singapore is already close to universal. Almost all local respondents, 96 percent, reported some level of AI usage within their organisations. Two-thirds said they had achieved success with AI initiatives so far, indicating strong early momentum and a willingness to invest in advanced technologies to improve efficiency, decision-making, and competitiveness.

However, this confidence weakens when organisations assess their ability to sustain value over time. Only 23 percent of Singapore respondents rated their organisation as industry-leading in readiness to achieve long-term return on investment from AI. This gap highlights a growing disconnect between deploying AI tools and building the operational foundations required to support them at scale.

The findings suggest that while many enterprises have moved beyond experimentation, fewer have fully aligned their data infrastructure, governance models, and security practices with the demands of AI-driven operations. As AI systems become more deeply embedded in business processes, this lack of readiness could limit the impact of future investments.

Data complexity and security emerge as strategic risks

As AI workloads expand, managing data is becoming more difficult for many Singapore organisations. The report indicates that data complexity is no longer viewed as a purely technical issue, but as a strategic risk with direct implications for governance, visibility, and cyber resilience.

More than half of Singapore respondents, 52 percent, said the complexity of their data environments makes it harder to detect a security breach. This highlights the link between infrastructure sprawl and increased exposure to cyber threats, particularly as data is spread across on-premise systems, cloud platforms, and hybrid environments.

Concerns extend beyond technical teams. Nearly two-thirds of respondents, 64 percent, agreed that if senior leadership fully understood how fragile their current data infrastructure is, it would keep them up at night. This points to a potential gap in understanding between executive decision-makers and those managing day-to-day data operations, which could slow efforts to address underlying weaknesses.

Risk-aware AI adoption and the push for stronger foundations

Despite these challenges, the research suggests that many Singapore enterprises are taking a more measured and risk-aware approach to AI adoption. Rather than focusing solely on rapid expansion, organisations are placing greater emphasis on governance, security, and operational discipline as AI systems begin to influence critical business decisions.

This shift reflects rising expectations around trust, reliability, and accountability. As AI plays a larger role in areas such as customer engagement, financial decision-making, and operational planning, weaknesses in data infrastructure become more visible and more consequential if left unresolved.

“AI success is no longer about experimentation alone. It depends on whether data environments are resilient, governed and trusted,” said Joe Ong, Vice President and General Manager for ASEAN at Hitachi Vantara. He added that while Singapore businesses are ahead in adoption, the next phase of progress will be defined by how effectively they manage complexity, security, and performance as AI scales.

The report concludes that closing the gap between AI adoption and sustained value will require coordinated, long-term investment in data foundations. Simplifying data environments, strengthening governance, and improving visibility across systems are likely to determine which organisations can move from early success to durable competitive advantage as AI investment continues to grow.