To date, artificial intelligence in finance has been treated as an experiment. Something to explore, pilot or tick the box, while the core of finance carried on as usual.
That era is over.
Recent survey data from senior finance leaders shows that AI is already embedded across much of the finance function. In a recent survey sponsored by MindBridge, 80 percent of finance teams reported they are actively using AI in operations today. Nearly one-third have scaled it across multiple workflows and more than a quarter now consider it mission critical.
Those figures matter, but not because they prove AI works. They matter because they reveal a deeper shift in how CFOs are thinking about their role.
From reporting outcomes to shaping them
Early AI initiatives in finance were understandably focused on efficiency. Most took the form of rules-based automation or narrow task support, aimed at accelerating reconciliations, speeding reviews and reducing manual effort in a function long measured by speed and accuracy.
That phase was necessary, but it was never the endgame. No CFO was hired to close the books faster forever.
What CFOs are pursuing now goes further. When asked about the primary impact they are targeting with AI, more than half of respondents pointed to improved forecasting, analysis and decision-making. Within their growing responsibilities, CFOs are adopting more advanced use cases for AI to complement and support their existing finance teams.
The mandate has shifted from doing the same work faster to seeing the salient details of the business sooner and more clearly than competitors.
That difference is not cosmetic. It signals a move away from using AI to optimize yesterday’s processes and a move toward using it to influence tomorrow’s decisions.
Finance teams already produce more data than most leaders can reasonably absorb. Dashboards are implemented, reports are timely, yet surprises persist. Margins fluctuate, risks surface too late and small issues quietly compound into material outcomes.
The irony is, finance has never had more information, yet critical details are still being missed or arriving too late.
The problem is not visibility in hindsight. It is visibility early enough to act.
Why timing has become the CFO’s real constraint
Gartner estimates that organizations lose between 3 and 8 percent of EBITDA annually due to poor decision-making. When polled, 91 percent of finance leaders said that estimate reflects their experience and 60 percent indicated they are using AI specifically to address that loss.
For many CFOs, the constraint is not intent but visibility: fragmented, manual reviews leave finance teams blind to unusual transactions, emerging fraud and subtle leakage across entities; gaps that only close when AI continuously examines the full population of transactions rather than a sampled few.
What CFOs recognize is that profit erosion rarely comes from a single bad call. It emerges from patterns that are easy to miss in the flow of daily operations: pricing inconsistencies, manual entry errors, missed discounts, process breakdowns that only become obvious after the period closes.
AI changes the equation when it is capable of examining the full population of financial and operational data continuously, rather than relying on periodic review or selective sampling. That level of analysis is fundamentally different from surface-level automation or text-based assistance. The value is not speed alone. It is the earlier signal, clearer context and the ability to intervene before outcomes are locked in.
A shift driven from the top
Another finding in the data underscores how central this shift has become. Half of respondents said AI initiatives in finance are being launched by the CEO or board, not by IT or innovation teams acting independently.
That reflects rising expectations of the CFO. Finance leaders are being asked to do more than validate results. They are being asked to guide the business with confidence, explain trade-offs clearly and support decisions that carry real consequences.
At the same time, CFOs are realistic about the obstacles ahead. Implementation cost, data quality and change management remain the most common challenges. These are not questions of belief in AI’s value. They are questions of execution discipline.
The bottom line
AI is no longer a side initiative inside finance. It is reshaping how CFOs fulfill an expanding mandate and implement decision quality in their organizations for greater business growth.
As expectations rise, finance leaders are being asked to influence outcomes, not just explain them after the fact. That requires insight that arrives early enough to matter, with enough clarity to stand behind. AI is becoming the mechanism that makes that possible.
The experiment is over and the technology demonstrated value at scale. What matters now is how effectively finance uses artificial intelligence at the moment decisions are being made.
