Confluent Study Finds Poor Data Infrastructure Is Derailing Singapore's AI Ambitions

Singapore companies are racing to deploy AI, but many are discovering that enthusiasm alone doesn't make up for shaky data foundations. A new report from Confluent — the 2026 Data Streaming Report — surveyed 4,625 IT leaders across 14 countries and found that nearly four in five Singapore IT leaders say inadequate real-time data infrastructure is preventing their organisations from scaling AI initiatives.

The numbers paint a sobering picture. While 75% of Singapore organisations are already deploying or piloting agentic AI solutions, the infrastructure underneath is struggling to keep up. Among Singapore respondents, 78% cited insufficient real-time data processing capabilities as a major barrier, 73% pointed to fragmented data ownership, and another 73% said they lack the skills and expertise to manage AI systems effectively. The result: 73% of Singapore organisations reported stalled agentic AI projects, and half said they had abandoned such work entirely.

These findings should give the local tech ecosystem pause. Singapore has positioned itself as a global leader in AI governance, and the government has poured resources into computing infrastructure, talent programmes, and regulatory frameworks. But the Confluent data suggests that for many businesses, the gap between AI ambition and operational reality remains wide — and the bottleneck isn't compute power or regulation, it's the quality and accessibility of data itself. As Shaun Clowes, Confluent's Chief Product Officer, put it: "Most organisations do not have an AI investment problem, they have a data problem."

The report also identified an interesting shift in investment priorities. Among Singapore respondents, data management and governance ranked as the top investment area (90%), overtaking AI and machine learning solutions themselves (85%). Ninety per cent of Singapore IT leaders said data streaming platforms can help address governance, risk, and compliance issues in agentic AI, and 92% said such platforms make data more trustworthy and discoverable. This suggests that the market is beginning to recognise what many infrastructure engineers have been saying for years: AI is only as good as the data pipeline feeding it.

Why it matters for Singapore: The Confluent study arrives at a moment when Singapore is doubling down on its Smart Nation ambitions, and it serves as a reality check. For policymakers, the findings highlight the risk of focusing too heavily on AI deployment metrics without tracking whether the underlying data infrastructure is ready to support it. For businesses, the message is clear: throwing more AI tools at problems without fixing the data plumbing underneath will lead to stalled projects and wasted investment. The companies that take data infrastructure seriously now will be the ones actually delivering results when the hype cycle settles.