Gsmart integrates AI into “the policies, data, and workflows treasury teams use every day,” Ripple said in a Thursday (Sept. 10) news release, with the expansion adding “new policy-governed capabilities” for tasks like forecasting, liquidity, risk, reconciliation and reporting.
“Enterprise adoption of AI agents is accelerating faster than the governance around it,” Ripple said, citing Gartner’’s projection that the average Fortune 500 company could have upwards of 150,000 agents in use by 2028.
At the same time, only 13% of companies think they have the right AI agent governance, a gap that “raises the stakes for how and where AI is deployed,” the release added.
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GSmart is designed to solve that gap by “separating financial calculation from AI interpretation,” Ripple said. Deterministic engines carry out the calculations behind financial decisions, while AI interprets policy, identifies patterns, and explains recommendations. Treasury teams maintain approval authority over each financial action.
“Every CFO is under pressure to embrace AI, but they’re equally responsible for ensuring every financial decision is explainable, governed and compliant,” said Renaat Ver Eecke, senior vice president of Ripple Treasury.
“Rather than asking customers to blindly trust an AI system, GSmart works within each organization’s own treasury policies to surface recommendations transparently, while ensuring humans remain in control of every decision. This isn’t simply AI-native treasury, but rather treasury-native AI.”
PYMNTS wrote last week about the use of AI agents in treasury functions, noting that agents are now carrying out “core treasury functions autonomously, from intraday liquidity decisions in wholesale payment systems to FX exposure forecasting and cash flow optimization.”
It’s a transition taking place within central bank research, corporate treasury teams and at banking giants like Goldman Sachs and Lloyds.
Goldman Sachs is developing autonomous agents powered by Anthropic’s Claude for core trade accounting and client onboarding, while Lloyds has committed to enterprise-wide agentic AI deployment in 2026. It is a shift that is “structural, not incremental,” PYMNTS wrote.
“Banks are no longer asking whether to integrate agentic AI into core treasury operations,” the report said. “They are asking how fast they can move from pilots to production, and what governance needs to be in place before they do.”
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