While Singapore-based organisations are accelerating AI adoption, critical gaps in data governance, human oversight and trust are holding back effective scaling of AI, according to Alteryx.
The is based on a survey conducted by Coleman Parkes from August 2025 to September 2025 and covered 1,400 business leaders and IT decision makers, including 175 respondents from Singapore.
Respondents came from the Americas; Europe, the Middle East and Africa; and the Asia-Pacific regions.
“Singapore’s AI ambitions are clear, and the momentum is real. But our research shows that organisations here recognise that technology alone is not enough,” said Philip Madgwick, regional VP for Asia at Alteryx.
“The leaders who will succeed in scaling AI are those who invest as much in the foundations as they do in the tools themselves,” said Madgwick. “That means trusted data, clear governance and keeping humans meaningfully in the loop. When those elements are in place, AI stops being a pilot and starts delivering real business impact.”
Results show that organisations in Singapore are broadly committed to AI, with nearly seven in 10 Singapore leaders reporting that they are using AI more in their roles than a year ago, outpacing the global average of 66%. Yet, the research reveals a series of structural gaps constraining real-world impact.
Only 27% of Singapore leaders fully trust AI for decision-making, with limited human oversight and review emerging as a top concern, particularly in customer-facing and highstakes use cases. While 79% trust AI for decision support in some capacity, the preference is clearly for AI-assisted, human-verified decisions over autonomous AI action.
Three in every five (60%) Singapore respondents cite centralised data governance as a missing capability in their data stack, compared to 53% globally. This raises questions about whether organisations have the structural foundations to assign clear accountability when AI decisions go wrong.
Also, data quality challenges are more prominent in Singapore than globally, with 49% citing data quality and accuracy issues as their top data stack challenge, versus 42% globally.
Further, 56% of Singapore organisations are experimenting with agentic AI versus 47% globally, yet most are yet to see meaningful impact, reflecting the difficulty of deploying autonomous systems responsibly without the right governance frameworks in place.
Alteryx said the research points to a clear set of foundations that organisations must get right.
One, keeping humans meaningfully in the loop, particularly for high-stakes and customer-facing decisions where oversight and accountability matter most.
Two, building centralised data governance structures that define clear ownership and responsibility as AI becomes more embedded in business decisions.
Three, investing in data quality as a prerequisite, not an afterthought, recognising that reliable AI outcomes depend entirely on the quality of the data feeding them.
And four, establishing governance frameworks for agentic AI before scaling, ensuring autonomous systems operate within clear boundaries and with appropriate human oversight.
