Treasury professionals face a balance between operational tasks and strategic growth contribution. Despite the potential of AI, many teams still rely on traditional methods. Integrating AI poses challenges, such as system compatibility and data quality. As treasury teams are increasingly lean, technology adoption is crucial for efficiency. The momentum for AI integration in treasury is building, with organizations looking to enhance their effectiveness.

Ask treasurers what they want to be known for, and rarely will you hear “my team reconciles faster than all others”. Rather, treasurers aspire to be the trusted advisor in the C-suite, helping to navigate market uncertainty, shape investment decisions, and guide the company towards growth. Yet for many treasury teams, the daily reality is still dominated by operational work: collecting data from multiple sources, patching gaps with spreadsheets, and producing reports under time pressure. This struggle between strategic ambition and operational burden is why AI adoption in treasury is poised for its hockey-stick moment.

Treasury professionals certainly see the promise in artificial intelligence: more than 7 in 10 believe that the technology can replace up to 25% of treasury tasks over the next five years. They are also clear about where AI can bring the most value – cash-flow forecasting , followed by receivables reconciliation, and FX risk management , areas where better prediction, faster handling, and smarter detection can directly lead to improved liquidity and reduced risk. However, there is a clear gap between promise and action: 1 in 2 companies have yet to deploy AI at all in treasury, and less than 1 in 10 have implemented AI into daily treasury workflows.

Source link