Singapore firms embrace agentic AI but lack data readiness

Research from SS&C Blue Prism has found that a third of organisations in Singapore plan to deploy agentic AI in the next year, but many do not have adequate data management systems in place to support its adoption.

The survey, which included responses from 1,650 global senior decision-makers, such as CEOs, CTOs, and IT leaders—of whom 150 were based in Singapore—explored how organisations are approaching next-generation artificial intelligence and the operational challenges involved.

According to the report's findings, the majority of Singaporean organisations (87%) see the main benefit of AI as its ability to disrupt existing processes and create entirely new ways of working. Over a third (33%) expect to begin using agentic AI for automation within the next 12 months.

Agentic AI refers to artificial intelligence systems capable of carrying out tasks independently, requiring far less human involvement after initial instructions are set. However, the research indicates that just over half (53%) of Singaporean organisations currently have robust and efficient data movement systems throughout their operations, an essential foundation for effective AI deployment.

Sunny Saha, Senior Vice President and General Manager of SS&C Blue Prism Asia Pacific, explained the specific requirements for leveraging agentic AI effectively. Saha said, "Agentic AI requires a vast amount of highly organised, standardized data so that it can perform tasks with less human interaction. Our research shows that just over half (53%) of Singaporean organizations have robust and efficient systems for moving data around their organization. Without these systems in place, you will not get the most out of the technology. You could also increase exposure to risks associated with data protection and sovereignty through activities such as accidental disclosures."

The interplay between automation, AI, and orchestration is identified by SS&C Blue Prism's research as crucial for progressing from raw organisational data to data suitable for use by AI applications. This covers both the training and operational phases of artificial intelligence, including digitising processes, and compiling and cleaning data from various sources.

Saha elaborated on how organisations can manage data more effectively to enable successful AI integration. He said, "The combination of automation, AI, and orchestration is proving to be the essential bridge between raw organizational information and AI-ready data. This spans the training phase of AI including digitising processes and assembling, collating, cleaning data from diverse silos; as well as the operational phase, managing all the upstream & downstream activities. This combination can also help with implementation of agentic AI guardrails – providing real-time monitoring and access for AI agents, as well ensuring all transactions are appropriately executed according to your organization's processes and protocols."

The potential operational improvements offered by these technologies come with heightened demands for data security and regulatory compliance, particularly given Singapore's status as a commercial hub with extensive cross-border transactions. Saha noted the importance of vigilance and a secure environment as AI adoption accelerates, stating, "The potential for this technology to improve how we work and how organizations serve their customers is significant. But enterprises in Asia must continue to be vigilant around security and compliance, given the dynamic regulatory environment and frequency of cross-border commerce. A robust data environment is essential to roll out AI solutions without compromising control over their data and operations."

The SS&C Blue Prism report's methodology involved a structured survey of senior technology leaders from the Americas, Europe, and Asia-Pacific. The responses provide insight into both the appetite for agentic AI adoption and the perceived challenges related to data infrastructure and preparedness across global markets.