Ripple has expanded GSmart, its treasury-native AI capabilities built into Ripple Treasury, adding policy-governed features across forecasting, liquidity, risk, reconciliation, and reporting. The expansion targets a governance gap that finance leaders face as enterprise AI adoption accelerates faster than the controls around it.
Gartner projects the average Fortune 500 company could have more than 150,000 AI agents in use by 2028, while just 13 percent of organizations believe they have the right AI agent governance in place today. For treasury teams managing critical financial operations, that gap raises the stakes for how and where AI gets deployed.
Separating calculation from interpretation
GSmart addresses the governance problem by separating financial calculation from AI interpretation. Deterministic engines perform the calculations behind financial decisions, while AI interprets policy, identifies patterns, and explains recommendations. Treasury teams retain approval authority over every 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, SVP 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."
What the launch includes
The launch adds three core capabilities. Orchestrated agents span forecasting and planning, liquidity, risk, reconciliation, and reporting. Each agent monitors its process, proposes a specific action, cites the policy clause behind it, and waits for approval before anything executes.
Knowledge Studio serves as the policy and governance layer, letting treasury teams define organizational controls that guide how AI capabilities operate. All proposed actions are checked against these controls before being up-leveled to a person. Analytics Studio with Ask GSmart provides a conversational assistant that helps treasury teams retrieve answers and insights from treasury data.
Adoption already underway
GSmart is already in production across Ripple Treasury's enterprise customer base. Sixty percent of eligible customers have enabled Risk Insights, which surfaces exposure anomalies and policy breaches. Forty-four percent are using Forecast Insights, which compares forecasted and actual cash flows to identify emerging liquidity gaps.
The expansion follows Ripple Treasury's launch of native digital asset capabilities earlier this year. Together, the tools give finance teams a single platform to view, predict, move, and earn on cash and digital asset balances. For CFOs evaluating how to bring AI into financial operations without losing control, this approach is directly relevant to the AI for Finance landscape. Finance leaders building internal AI expertise can also explore an AI Learning Path for CFOs.
Why this matters for finance professionals
GSmart's design choice, deterministic engines for calculations with AI limited to interpretation and explanation, offers a concrete template for how treasury teams can adopt AI without surrendering auditability. If your organization is evaluating AI agents for financial processes, the key question is whether the system separates computation from recommendation and keeps approvals in human hands. GSmart's early adoption numbers suggest enterprise treasury teams are willing to move on governed AI when the controls are built in from the start.
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