A new study of Singapore business and analytics leaders indicates a significant gap between organisations’ aspirations to drive value from data and the actual state of their data infrastructure, posing challenges for those aiming to scale artificial intelligence initiatives.

Mounting data pressures

The research surveyed over 7,600 business and analytics decision makers globally, including 200 from Singapore. It found that 77% of Singapore business leaders are under increasing pressure to boost business value through the use of data. Despite strong intent, only 54% of business leaders see their organisations as data-driven, while 63% of analytics leaders acknowledge difficulties in leveraging data to advance organisational priorities.

Less than half of leaders report the ability to generate timely insights from data. Further, 59% of Singaporean analytics leaders said their companies sometimes or frequently draw incorrect conclusions from data lacking business context.

AI ambitions clash with data realities

The rapid rise of artificial intelligence is intensifying scrutiny of existing data strategies. AI has moved to the top priority for Singapore’s data and analytics leaders, up from 10th place last year. Despite this focus, 91% of analytics leaders surveyed believe their current data strategies require a complete overhaul to support AI ambitions.

Pressure to implement AI quickly is widespread, with 86% of data and analytics leaders concerned about the need to adopt these technologies rapidly. However, over a third of them are not fully confident in the accuracy and relevance of AI outputs, a concern attributed to disconnected or outdated underlying data. On average, leaders estimate that 27% of their organisation’s data is untrustworthy.

Risks of unreliable outputs

Many organisations deploying AI are already experiencing negative consequences. Of those with AI systems in production, 84% of analytics leaders have faced inaccurate or misleading outputs. Additionally, nearly two-thirds of leaders involved in training or modifying AI models reported significant wasted resources as a result of using substandard data.

“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,” said Marc Benioff, CEO, Salesforce.

Siloed data remains a obstacle

Accessibility continues to be a barrier to effective data use. Singapore analytics leaders estimate that 21% of company data is siloed, inaccessible, or otherwise unusable. Significantly, 78% believe that key business insights are likely to be found within this trapped segment of data.

The ramifications of data fragmentation are substantial. More than seven in ten Singapore analytics leaders report that siloed information reduces AI capabilities, clouds customer understanding, inhibits personalisation, and creates missed revenue opportunities. On average, enterprises are juggling data from hundreds of business applications, with only 29% of these connected, compounding the challenge.

Integration and governance efforts

Organisations in Singapore are turning to technical solutions like zero copy data integration. This approach allows use of data across multiple databases without the need to move or reformat it. The report notes that Singapore companies using this method are significantly more likely to succeed both in customer experience and AI projects compared to those that do not.

Usability remains another challenge, with 72% of analytics leaders highlighting the risk of error when translating business questions into technical database queries. Almost all business leaders surveyed expressed a desire for natural language tools to improve their ability to obtain data-driven answers.

On governance, only 40% of analytics leaders state their organisations have formal data governance frameworks in place. A substantial 93% agree that the rise of AI requires entirely new approaches to both data governance and security.

“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 Gavin Barfield, Vice President & Chief Technology Officer, Solutions, ASEAN, Salesforce.