A recent study by SS&C Blue Prism titled The Global Enterprise AI Survey 2025, reveals that 87% of organisations in Singapore view artificial intelligence (AI) as a transformative force capable of disrupting traditional processes and creating entirely new ways of working. Notably, 33% of these organisations plan to adopt agentic AI within the next year to automate various tasks.
As the interest in agentic AI grows, the report highlights a critical requirement: organisations must enhance their data management protocols to fully leverage this technology.
Sunny Saha, SVP and general manager of SS&C Blue Prism Asia Pacific, emphasised that agentic AI relies on well-organised and standardised data to operate effectively. However, only 53% of Singaporean organisations currently possess robust systems for managing data flow.
Saha noted, "Without efficient data systems, companies risk not only underutilising AI capabilities but also increasing exposure to data protection risks. These include accidental disclosures and breaches of data sovereignty."
The integration of automation, AI, and orchestration is becoming essential for bridging the gap between raw data and AI-ready information. This combination not only supports the training of AI models by digitising and cleaning data from various silos but also manages operational activities effectively.
Moreover, it enables the implementation of crucial guardrails for agentic AI, ensuring real-time monitoring and adherence to organisational protocols.
The potential applications of agentic AI in enhancing operational efficiency and customer service are substantial. However, as organisations in Asia adopt these technologies, they must remain vigilant regarding security and compliance.
The region's dynamic regulatory environment and the complexities of cross-border commerce necessitate a robust data management strategy to safeguard operations and maintain control over sensitive information.
In conclusion, while the enthusiasm for agentic AI in Singapore is promising, the path to successful implementation hinges on addressing foundational data challenges. Organisations that prioritise these elements will be better positioned to harness AI's full potential, transforming not only their internal processes but also the overall customer experience.
