AI integration in corporate treasury management

The corporate treasury sector is experiencing a technological transition toward artificial intelligence and automation. Research indicates a significant shift in foreign exchange (FX) execution, with manual and voice-based methods expected to decline sharply as embedded FX and API-driven workflows grow.

Studies by the Bank for International Settlements and the Bank of Canada have demonstrated that generative AI agents can replicate prudent liquidity management practices, such as prioritizing urgent payments. This evolution allows treasury teams to move from reactive, spreadsheet-based tasks toward strategic roles in risk management and liquidity optimization.

Following its $1 billion acquisition of GTreasury, Ripple has expanded its GSmart suite of policy-governed AI agents within the Ripple Treasury platform. These tools assist enterprise finance teams with cash forecasting, liquidity planning, risk management, reconciliation, and reporting.

To address governance concerns, the platform utilizes a dual-layer architecture that separates deterministic engines, which perform core financial calculations, from AI agents that interpret company policies and identify data patterns. This structure ensures that AI agents cannot execute moves independently; they can flag potential policy breaches and provide explanations, but the system requires human approval for all financial transactions. Ripple reports that 60% of eligible customers currently use the Risk Insights feature, while 44% utilize Forecast Insights.