Treasury teams in Singapore are shifting to AI implementation from experimentation, as they are found to be already using artificial intelligence to support day-to-day activities such as reconciliation, invoice matching, forecasting and know-your-customer (KYC)-related work.
In a study by HSBC, it was revealed that seven in ten treasurers expect AI to be extremely or very useful within next three years.
But, it was also found that while confidence in AI remains strong, expectations have become more measured as businesses gain practical experience and assess what is required to integrate and scale the technology effectively.
The study, which polled 680 treasury and finance professionals, highlights the practical challenges businesses face as they move from experimentation towards implementation.
According to HSBC, system integration was identified as the leading barrier to AI adoption by 70% of Singapore participants, followed by a lack of expertise at 59%.
For businesses seeking to make real-time treasury a reality, 39% cited technology and cybersecurity risks, while 38% identified both securing budget approval and gaining stakeholder support as key challenges.
For APAC CFOs and finance leaders, HSBC’s findings show a shift in the AI agenda from experimentation to practical implementation, with the focus increasingly on whether the technology can deliver measurable improvements in treasury operations.
While AI is already supporting activities such as reconciliation, invoice matching and forecasting, system integration remains a significant hurdle.
For finance leaders, these challenges underscore the need to assess how AI can integrate with existing financial systems, strengthen cash-flow visibility and improve forecasting accuracy without compromising cybersecurity, data governance or operational resilience.
As enterprises look to scale AI adoption, CFOs will also need to consider the investment required to move from pilot projects to sustainable, business-wide implementation.
This includes establishing a clear business case, securing stakeholder support and ensuring that finance teams have the capabilities to use AI effectively.
