Treasury has spent years solving for visibility. Bank connectivity has improved, cash positions have become more centralized, and financial exposures are easier to measure than ever before. Yet many treasury teams still make liquidity decisions through a combination of spreadsheets, manual analysis, and organizational coordination. As a result, the challenge facing treasury is no longer data availability, it’s decision velocity. In an environment where market conditions can change overnight, treasury leaders are expected not only to understand liquidity, but to anticipate risk, optimize capital allocation, and contribute directly to strategic business outcomes.

As part of the autonomous finance movement, autonomous treasury is emerging as an operating model in which AI helps treasury organizations move beyond reporting on liquidity to actively managing it. The timing isn’t accidental. According to research conducted by Zanders, data and functional silos remain the number one barrier preventing treasury from playing a more strategic role, even as treasury priorities increasingly align with broader CFO priorities. Treasury leaders are being asked to do more than provide visibility. They are being asked to help shape business outcomes.

And let’s be clear that the goal is NOT to replace treasury professionals. The goal is to allow these incredibly valuable (human) resources to spend less time gathering data and more time in making high-value decisions.

To get there, organizations need five foundational capabilities.

1. Real-time cash visibility

It’s pointless to try to automate decisions if there isn’t trust in the underlying view of cash. Many treasury teams still operate with fragmented banking relationships, disconnected systems, and delayed reporting cycles. The result is a treasury function that spends valuable time answering a basic question: "What is our actual cash position?"

Autonomous treasury starts with a single, trusted view of liquidity across banks, accounts, entities, and currencies. When treasury has real-time visibility, decisions become proactive rather than reactive and this capability is the foundation for everything that follows.

2. Predictive cash forecasting

While historical reporting explains yesterday, what is clear that today’s treasury needs to understand tomorrow. Modern forecasting models combine trusted operational, financial, and market data to identify emerging liquidity needs before they become funding events. The shift is subtle but important.

The importance of forecasting continues to grow because forecasting and risk management are becoming increasingly interconnected. Citing research by Zanders, 31% of multinational organizations believe “AI-driven cash forecasting will have the greatest impact on future FX risk management.” The implication is clear, that the better an organization can predict future liquidity needs, the better positioned it becomes to manage financial risk. This shift allows treasury teams to accelerate their abilities to reduce idle cash, improve borrowing decisions, and respond earlier to potential shortfalls. Forecasting becomes less about producing a report and more about options and optimization.

3. Intelligent liquidity optimization

Knowing “real-time” where cash will be is valuable but knowing the best use of that cash is even more valuable.

As forecasting accuracy improves, Treasury can begin optimizing liquidity dynamically. Questions that previously required manual analysis become candidates for intelligent recommendations:

• Should excess cash be invested?
• Should surplus liquidity be redeployed?
• Should intercompany funding be adjusted?
• Is short-term borrowing necessary?

This is where Treasury begins shifting from visibility to trusted orchestration. AI is an increasingly powerful solution to surface opportunities, but treasury maintains control and defines the policies, limits, and business priorities.

4. Continuous risk hedging

For many global organizations, financial risk changes daily while hedge decisions happen periodically. Unfortunately, that creates exposure gaps as foreign exchange, interest rates, and commodity markets rarely wait for scheduled review meetings.

The urgency is understandable. According to the PwC Global Treasury Survey referenced in recent treasury thought leadership materials, 83% of treasurers cite foreign exchange risk as their number one concern. In that environment, quarterly reviews and static hedging strategies are increasingly difficult to justify. Treasury organizations need earlier visibility into exposures and greater agility in responding to changing market conditions.

The next generation of treasury platforms is moving toward continuous monitoring of exposures and intelligent identification of hedging opportunities. Rather than searching for risks after they materialize, treasury can identify:

• Emerging FX exposures
• Potential over-hedge situations
• Liquidity concentration risks
• Funding mismatches

Ask any treasury team that managed currency exposure during a period of significant market volatility. The challenge was rarely identifying the risk after it happened. The challenge was identifying the risk early enough to do something about it.

5. AI agents that drive action

Most organizations already have dashboards but what they lack is execution support. AI agents represent a shift from systems that simply report information to systems that can recommend, coordinate, and potentially execute treasury activities within defined governance frameworks.

Imagine receiving:

"Projected USD liquidity shortfall in three days. Recommended funding source identified. FX exposure exceeds policy threshold. Suggested action ready for review."

Treasury remains accountable but AI dramatically reduces the time needed to move from insight to action and that is the essence of autonomous treasury. This distinction is important because treasury isn’t looking for more dashboards. It’s looking for a faster path from awareness to execution. Autonomous agents help close the gap between identifying an issue and responding to it within established controls and governance policies.

Don’t automate the chaos

Every conversation about autonomous finance eventually reaches the same conclusion: AI amplifies maturity, but it does not replace it. This reinforces an important lesson for treasury leaders: successful autonomy starts with trusted data, strong governance, and disciplined processes. Taken together, these five capabilities represent a progression. Organizations typically begin with visibility, mature into forecasting and optimization, and eventually establish the operational foundation required for autonomous decision support.

Organizations with inconsistent processes, poor data quality, or fragmented treasury operations often expect AI to solve foundational challenges. In reality, autonomous treasury depends on trusted data, clear policies, and well-defined governance. The companies that will benefit most are not those pursuing autonomy first and they are the ones building the operational foundation that makes autonomy possible.

Final thoughts

The future of treasury isn't about handing control to algorithms, instead it’s about enabling treasury teams to operate at a higher level.

• Real-time visibility provides awareness.
• Predictive forecasting creates foresight.
• Liquidity optimization improves efficiency.
• Continuous hedging strengthens resilience.
• And AI agents help convert decisions into action.

Taken together, these capabilities point to a future where liquidity management becomes increasingly autonomous, allowing treasury professionals to focus less on administration and more on strategy.

Treasury has spent decades trying to improve information visibility. The next decade will be about accelerating and augmenting decisions.

Organizations that combine trusted data, predictive intelligence, continuous risk monitoring, and governed automation will be better positioned to move faster, manage risk more effectively, and unlock greater liquidity value.

The future of treasury isn’t autonomous because humans disappear. It becomes autonomous because treasury professionals finally have the tools to operate at their best.

Come join the conversation at SAP Connect, October 5-7 in Las Vegas.  Session FIN1639 “SAP's Product Vision for Treasury & Working Capital Management” is scheduled for Wednesday at 2:30 or will be available virtually.

https://www.sap.com/events/connect.html