The 2025 Upgrades That Pushed Treasury to the Center of the Enterprise

When leaders outside of finance think of treasury management … they typically don’t.

For much of its history, the enterprise treasury function has been taken at face value as something operational, essential and largely invisible. But, as 2025 proved, that mindset is coming to an end.

Looking ahead to 2026, treasury has come to sit at the center of the enterprise, increasingly indistinguishable from a real-time financial command center. Predictive cash forecasting, automated risk management, natural language queries and real-time intelligence have become table stakes as once-daily manual tasks like cash positioning start to move at machine speed.

The forces reshaping this evolution are familiar: globalization, volatility, digitization. But their combined effect is profound. As economic uncertainty persists and complexity increases, the evolution of treasury management is moving to the center of corporate strategy.

Across the finance function of modern enterprises, cash positioning happens continuously in the background. Risk is monitored and managed in real time. Forecasts update themselves as conditions change. And CFOs interact with treasury not through static reports, but through dynamic, conversational intelligence.

The shifts that took place throughout the year across treasury management system (TMS) innovation were not about replacement, of systems or of workforces, but about augmenting existing capabilities and unlocking new ones. This was powered by investments in financial infrastructure and data-readiness. By offloading execution to systems and elevating insight, treasury became a strategic nerve center capable of informing decisions across the enterprise.

See also: Making Sense of the Liquidity Hub Treasury Model

The Rise of Platform Thinking Across Enterprise Treasury Management

If there is a single capability that defines modern treasury, it’s predictive cash forecasting. Long the Achilles’ heel of finance teams, forecasting has historically relied on spreadsheets, static assumptions and manual inputs from across the organization. The result was often a rearview-mirror view of liquidity—useful for compliance, less so for decision-making.

“One thing that all treasury organizations are looking for is visibility into their global activity,” Sebastian Sintes, director of transactional FX at Bank of America, told PYMNTS in an interview posted Sept. 8.

“For the corporate organizations that have been making some heavy investments into their system infrastructure, that return on that investment is going to start to be felt in the upcoming years…,” he added.

Leading platforms don’t just predict shortfalls; they suggest actions. A looming liquidity gap might trigger recommendations to draw on a revolver, delay a payment or rebalance internal cash pools. Treasury, in effect, is moving from forecasting outcomes to shaping them.

The PYMNTS Intelligence report “Why Treasurers’ Influence Matters” found that treasurers with high levels of influence are more likely to report that their companies have predictable cash flows, expect revenue to increase and are agile in responding to shifting market conditions.

Underlying many of these upgrades is a broader architectural shift. Treasury systems are evolving from standalone applications into platforms designed to integrate seamlessly with enterprise resource planning (ERPs), banks, FinTech providers and analytics tools. Artificial intelligence is powering this shift.

“It’s no longer a nice-to-have,” Steve Wiley, vice president of product management at FIS, told PYMNTS in an earlier interview. “Artificial intelligence is a must-have, and that’s happened very, very quickly …  instead of using traditional historical-based models, treasury departments are expecting generative AI to project cash flows. And that’s already the new normal.”

“Seventy-five percent of knowledge workers, and those are people in the office of the CFO, now use AI at work, and half of those started using it in the last year,” Wiley added. “There’s an expectation now that AI-based solutions will be embedded within these financial products.”

Application programming interfaces (APIs) are central to this transformation. They enable real-time data flows, reduce reliance on batch files, and make it easier to plug in new capabilities as they emerge. For treasury teams, this modularity is critical: it allows innovation without wholesale system replacement.

Read also: AI, Cyber Risk and Payments Monetization Put Treasury at the Center of Finance

What the Treasury of the Future Looks Like

Technology alone does not define the future of treasury; people do. This year’s upgrades have accelerated that shift. Treasury teams are spending more time analyzing scenarios, advising on capital allocation and partnering with the business. The function is becoming less about control and more about insight.

After all, the ongoing shift to real-time liquidity does not replace traditional treasury tasks. It changes how teams do them, Stephen Randall, global head of liquidity management Services at Citi, explained to PYMNTS in an interview published on Monday (Dec. 22).

He envisions accounts that automatically draw funding when balances fall below thresholds, transforming manual sweeps. At Citi, this is becoming a reality, and tokenization is helping to allow those instructions to run continuously, he said. For example, Citi unveiled Citi Real-Time Funding, (RTF) an automated solution for clients to move liquidity across their Citi accounts, in real time and across borders, to fund payments. RTF automates a real-time transfer so that they can make the payment when their business needs it without manually processing the account funding.

Taken together, the upgrades over 2025 point to a clear vision of the treasury function of the future. It is predictive rather than reactive, automated rather than manual, and integrated rather than siloed. It operates at machine speed but remains grounded in human judgment.