PYMNTS Study Finds CFOs Turn to Agentic AI for Savings and Cash Flow
What if a way to track, forecast and model cash, credit, debt and investments could make your company smarter and stronger? What if the corporate finance function unlocked hidden savings and faster, more efficient ways to strategically allocate money toward operations and growth? And what if a rapidly evolving technology could do all of that autonomously with minimal human interaction, independently making decisions and taking actions on your behalf based on the predefined inputs and instructions you give it?
Agentic artificial intelligence promises to shift much of the CFO function away from in-the-moment numbers-crunching, much of it manual, time-consuming and on spreadsheets, toward forward-looking, big-picture jobs like scenario modeling and strategic analysis.
But allowing an algorithm, not your finger on a mouse, to send millions of dollars to a supplier in an instant is a high-stakes, high-risk endeavor. So is allowing an agent to pull the trigger on shifting big dollars from one budget bucket to the next. That’s why CFOs aren’t yet all-in on turning over the reins.
Here’s a look at the top 10 ways PYMNTS Intelligence research finds CFOs using agentic AI, in The CAIO Report “CFOs Push AI Forward but Keep a Hand on the Wheel.”
1. Move money where it’s needed, when it’s needed
Time to budge the budget. The highest-ranked use case for agentic AI is dynamic budget reallocation based on fresh cost data. Roughly 43% of CFOs expect a high impact from using agents in some form to handle this function, with another 47% expecting moderate impact. Instead of annual or quarterly budget resets, agentic AI can continuously scan real-time spending patterns, flag overruns and shift funds toward higher-priority areas. For CFOs under pressure to do more with what they have, the promised payoff is fewer surprises, fewer fire drills and more discernment and control over how every dollar is deployed.
2. Turn forecasting into a live feed
You snooze, you lose. Agentic AI can continuously update forecasts as new data arrives and run scenarios on demand, turning forecasting into a living dynamic process rather than a static report. Nearly 1 in 3 CFOs predict agentic AI will have a high impact on producing real-time forecasts and “what-if” simulations, with many more (4 in 10) seeing only a moderate impact. “Folks are just starting to understand that AI isn’t just automation with ‘kind of sexier’ marketing,” Finexio CEO and Founder Ernest Rolfson told PYMNTS in December. “Embracing it as infrastructure lets you use your data as a strategic asset.”
3. Time cash moves more intelligently
Cash shouldn’t sit still. Seven in 10 firms already use at least one AI tool to manage cash flow, according to the PYMNTS Intelligence report “Time to Cash: A New Measure of Business Resilience.” About 1 in 3 CFOs expect high impact from agents that recommend when to hold cash, when to pay early and when to delay things. By monitoring cash positions and obligations in real time, agentic AI can suggest small timing adjustments that add up to meaningful liquidity gains.
4. Speak one numbers language across the company
One company, dozens of dialects. Thirty-five percent of CFOs expect strong impact from agents that standardizes the language and presentation of accounts and intercompany transactions. This is especially valuable after mergers or technology switches, when inconsistent account languages can slow reporting and muddy comparisons.
5. Get data ready without the busywork
Like a disaster meetup with your friend’s cousin from out of town, data can arrive messy and late. Another 35% CFOs expect high impact from AI that ingests, cleans and maps data across systems. This use case is less glamorous, but foundational. Faster, cleaner data feeds every downstream insight, from forecasting to compliance.
6. Take the pain out of intercompany reconciliation
Numbers can have a hard time playing together nicely in the sandbox. Matching intercompany transactions is a classic pain point, especially for global firms. About 37% of CFOs see high impact from AI that can match transactions and resolve exceptions automatically. By learning normal patterns and flagging only true mismatches, agentic systems reduce close times and free staff from manual reconciliation work.
7. Explain the data without getting bogged down in spreadsheets
Always be thinking of what’s next. Once the books close faster, the next bottleneck is explaining results. Variance analysis is essential but time-consuming. Four in 10 CFOs expect high impact from AI that not only runs the analysis but also generates explanations of what changed and why. This shifts finance teams away from spreadsheet archaeology and toward interpretation and decision-making.
8. Keep the numbers clean and credible
Cleanliness is next to godliness. Data that’s not messy underpins everything in finance, yet it’s often fragile. Another 40% of CFOs expect agentic AI to have a high impact on data governance and integrity alerts. These systems can spot anomalies, missing fields or conflicting records across sources, helping finance leaders trust the numbers they present to boards and investors.
9. Catch problems before auditors do
Preventing potential problems from regulatory violations is always a top concern, and CFOs are turning to AI to watch the store. Around 42% expect high impact from agentic systems that monitor controls and surface policy violations. Instead of periodic audits or after-the-fact reviews, agentic AI can flag issues as they arise, giving teams time to fix problems before they become costly.
10. Make finance systems actually work together
Corporate finance is like a quilting bee where different business units need to all work together. About 42% of CFOs see high impact from AI that can coordinate workflows across enterprise resource planning, accounts receivable and payable, and treasury platforms. Finance teams still spend enormous time stitching together processes that live in different systems. Agentic AI acts as the red thread, routing tasks, syncing data and reducing delays that come from handoffs between tools. That’s why i2c Founder and CEO Amir Wain sees the technology as “moving beyond reactive responses to proactive action, autonomously resolving routine tasks without human escalation, freeing up valuable resources.”
At PYMNTS Intelligence, we work with businesses to uncover insights that fuel intelligent, data-driven discussions on changing customer expectations, a more connected economy and the strategic shifts necessary to achieve outcomes. With rigorous research methodologies and unwavering commitment to objective quality, we offer trusted data to grow your business. As our partner, you’ll have access to our diverse team of PhDs, researchers, data analysts, number crunchers, subject matter veterans and editorial experts.
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