Poor Data Infrastructure Is Stalling AI Growth in Singapore, Confluent Report Finds
Source: Frontier Enterprise
Nearly four in five Singapore IT leaders say inadequate real-time data infrastructure is preventing their organisations from scaling AI, according to Confluent's 2026 Data Streaming Report. The survey found 78% face infrastructure gaps despite 75% deploying agentic AI solutions, with 73% reporting stalled projects as a direct result.
Singapore has positioned itself as a global laboratory for AI governance and enterprise adoption, but there is an uncomfortable reality beneath the headlines. The tools Singaporean organisations are using to build and deploy AI are not ready for the scale they are targeting. According to Confluent's 2026 Data Streaming Report, nearly four in five IT leaders here say inadequate real-time data infrastructure is preventing their organisations from scaling AI initiatives effectively.
The report, which surveyed 4,625 IT leaders across 14 countries including Singapore, found that 78% of respondents had encountered at least three significant challenges when scaling AI. The biggest bottleneck is real-time data processing infrastructure, cited by 78% of Singapore IT leaders. Fragmented data ownership affects 73%, and the same proportion identified insufficient skills and expertise in managing AI systems. These constraints are not hypothetical — 73% of Singapore respondents reported that agentic AI projects had stalled as a direct result, with half abandoning the work entirely.
The enthusiasm is clearly there: 75% of Singapore organisations are already deploying or piloting agentic AI solutions. But the infrastructure gap is widening faster than most companies can bridge it. A striking 95% of Singapore respondents said they either experience or anticipate problems with data infrastructure and quality, with the same proportion citing legacy system integration as a barrier. A further 93% identified large language model reliability as a concern, suggesting that even when infrastructure is sorted, trust in AI outputs remains a separate, unresolved issue.
"Businesses across Singapore are rapidly embracing AI, strengthening the country's position as a global leader in AI governance," said Greg Taylor, Confluent's Senior Vice President for APAC. "But as AI systems become more embedded in business processes, trust cannot come from regulation alone." Taylor's point is worth sitting with: Singapore may lead on governance frameworks and ethical guidelines, but data infrastructure is where the rubber meets the road, and that is where the weakest links are showing.
Why it matters for Singapore: The gap between AI ambition and data readiness is not a future problem — it is a present one. Singaporean businesses are spending heavily on AI, but without parallel investment in real-time data infrastructure, those projects will stall, and the country's edge as a regional AI hub could erode. The numbers in this report suggest that fixing data infrastructure is not a follow-up item — it is the prerequisite that should come first.
