91 percent of data and analytics leaders in Singapore say their data strategies need a complete overhaul before their artificial intelligence (AI) ambitions can succeed, Salesforce‘s study revealed Thursday.
According to the firm’s latest State of Data and Analytics report, 77 percent of business leaders in Singapore 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.
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 organizations back from realizing the technology’s full potential, and fulfilling their vision of becoming agentic enterprises,” said Gavin Barfield, Vice President & Chief Technology Officer, Solutions, ASEAN, Salesforce.
“Singapore organizations 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,” he added.
According to the study, 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 #10 priority among Singapore respondents in 2023 to the #1 priority this year.
As a result, 86 percent of data and analytics leaders in Singapore feel pressured to implement AI quickly.
Yet, 36 percent aren’t fully confident in the accuracy and relevance of their AI outputs, likely because of the disconnected, out-of-date data it draws from.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 percent 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 percent) of their organizational data is untrustworthy.
Meanwhile, 84 percent 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 percent) at companies training or fine-tuning their own models report they’ve wasted significant resources doing so with bad data.
“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,” said Salesforce Chief Executive Officer Marc Benioff.
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.”