There is a fundamental disconnect between businesses’ data demands and their data reality, which can hinder their progress toward becoming agentic enterprises, according to a report from Salesforce.
Data in this report are from two double-anonymous surveys conducted from June 27 through August 13, 2025. The first survey generated 3,800 responses from analytics and IT decision makers from 18 different countries across North America, Latin America, Asia-Pacific and Europe, including Singapore.
The second survey generated 3,852 responses from line-of-business leaders from the same countries. More details can be found in the report. Cultural bias impacts country-level survey results.
Among business leaders in Singapore, 77% say they’re under growing pressure to drive business value with data. While business leaders are eager to use AI for insights and productivity, their technical counterparts worry a new approach to data and analytics is needed.
In fact, 91% of data and analytics leaders in Singapore say their data strategies need a complete overhaul before their AI ambitions can succeed.
To close the gap, savvy technical leaders are focusing on the fundamentals: timely, context-rich data, stronger governance and zero copy architectures that unlock trapped, distributed data regardless of where it resides. On their journey to becoming agentic enterprises, they’re also embracing emerging solutions like agentic analytics that bring reliable insights into the flow of work.
“Agentic AI is the most powerful enabler of business transformation today, ushering unprecedented productivity, customer connection and growth. Yet, fragmented data and inconsistent governance continue to hold organisations back from realising the technology’s full potential, and fulfilling their vision of becoming agentic enterprises,” said Gavin Barfield, Salesforce VP and CTO of solutions in ASEAN.
“Singapore organisations facing mounting pressure to expand their AI capabilities must first get their data foundation in order. Unifying disparate data, and building robust governance will be critical to unlocking real business value from AI,” said Barfield.
Findings show that more than half (54%) of business leaders in Singapore describe their organisations as data-driven. Yet nearly two-thirds (63%) of data and analytics leaders say their companies struggle to drive business priorities with data, exposing a gap between data maturity perceptions and reality.
Less than half (46%) of business leaders in Singapore say they can reliably generate timely insights.
Over half (59%) of data and analytics leaders in Singapore say their companies occasionally or even frequently draw incorrect conclusions from data with poor business context.
Also, AI has quickly become the top data priority — and the biggest stress test for existing data foundations. In 2023’s State of Data and Analytics report, expanding AI capabilities rose from the No. 10 priority among Singapore respondents in 2023 to the No. 1 priority this year.
As a result, 86% of data and analytics leaders in Singapore feel pressured to implement AI quickly.
Yet, 36% aren’t fully confident in the accuracy and relevance of their AI outputs, likely because of the disconnected, out-of-date data it draws from.
While 88% of data and analytics leaders theoretically agree that AI’s outputs are only as good as its data inputs, their reality is a bit more complicated. Data and analytics leaders estimate that over a quarter (27%) of their organisational data is untrustworthy.
Further, 84% of data and analytics leaders in Singapore with AI in production say they’ve experienced inaccurate or misleading AI outputs.
Nearly two-thirds of Singapore data and analytics leaders (66%) at companies training or fine-tuning their own models report they’ve wasted significant resources doing so with bad data.
