Salesforce has released new findings from its latest State of Data and Analytics report, highlighting a widening gap between what organisations in Singapore want to achieve with data and what their current systems can support. The study draws on insights from 3,800 analytics and IT decision makers and more than 3,800 business leaders worldwide, including 200 respondents from Singapore.
According to the report, 77% of business leaders in Singapore face mounting pressure to show tangible business results from data. While many hope to use AI to improve decision-making and productivity, technical leaders remain concerned that existing data foundations are not fit for purpose. A significant 91% of data and analytics leaders in Singapore believe their current strategies require a complete overhaul before AI initiatives can succeed.
Salesforce notes that organisations are focusing increasingly on timely and context-rich data, stronger governance, and zero copy architectures that allow access to distributed data without moving or duplicating it. These efforts are seen as essential steps towards building agentic enterprises capable of using AI agents to deliver real-time insights at scale.
“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, Vice President and Chief Technology Officer, Solutions, ASEAN at Salesforce. He added that “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.”
Data maturity gaps challenge AI adoption
Although 54% of business leaders in Singapore consider their organisations data-driven, nearly two-thirds of data and analytics leaders say they struggle to advance business priorities through data. Only 46% of business leaders report being able to reliably generate timely insights. The report also finds that 59% of data and analytics leaders believe their companies often draw incorrect conclusions due to data lacking proper business context.
AI has become the top data priority for organisations in Singapore, rising from tenth place in 2023 to the number-one focus this year. This shift has placed additional stress on already strained data foundations. Around 86% of data and analytics leaders in Singapore say they feel pressured to implement AI quickly, yet 36% admit they are not fully confident in the accuracy or relevance of their AI outputs.
The uncertainty stems from concerns over disconnected and outdated data. While 88% of leaders acknowledge that AI output quality is closely tied to input quality, they estimate that 27% of their organisational data is untrustworthy. The consequences are significant. Among companies with AI in production, 84% report experiencing inaccurate or misleading outputs, and 66% say they have wasted resources training or fine-tuning models on bad data.
Salesforce CEO Marc Benioff emphasised the urgency of addressing data quality during his Dreamforce keynote. “Agentic AI isn’t the next technology, it’s the next revolution. AI agents handle routine tasks so humans can focus on creativity, relationships, and impact,” he said. However, he warned that “to truly get the most value and context from AI models, you’ve got to get your data right. You have to get to more integrated solutions. You have to get the priorities right. You have to get the governance right.”
Unlocking value by resolving data silos
The report highlights the scale of the data fragmentation challenge. Although 9 in 10 data and analytics leaders believe unified data is essential for meeting customer expectations, concerns over inaccessible or siloed data continue to rise. The average enterprise now uses 897 applications, but only 29% are connected. This scattering of data across systems creates significant barriers to AI adoption.
Respondents in Singapore estimate that 21% of their company’s data is siloed or unusable. More worryingly, 78% believe their most valuable insights sit within that inaccessible portion. The impact is widespread, with over 70% citing reduced AI capabilities, incomplete customer views, reduced personalisation, and missed revenue opportunities as direct consequences.
To address this, 58% of organisations in Singapore are turning to zero copy data integration. This approach allows them to access multiple databases simultaneously without duplicating or moving data. The findings suggest that companies adopting zero copy are 74% more likely to deliver strong customer experiences and 182% more likely to succeed with AI initiatives.
The study also points to natural language interfaces, such as agentic analytics, as a way to reduce data literacy barriers. Around 72% of data leaders say translating business questions into technical queries remains error-prone, while 97% of business leaders believe they would perform better if they could ask data questions using natural language.
Governance remains a pressing issue. Only 40% of data and analytics leaders in Singapore have formal data governance frameworks in place. At the same time, 93% agree that AI requires entirely new approaches to governance and security due to its growing complexity and scale.
