“Every CFO I talk to right now is doing two things simultaneously: signing off on AI spend and quietly wondering if they’ll regret it,” said Zwick. “The worry is a feature, not a bug.”
A recent Billtrust survey reveals that 65% of finance leaders are dedicating 10% or more of their 2026 budgets to AI and automation initiatives. At the same time, 59% of those leaders believe the current wave of AI investment could be a bubble that won’t deliver sustained long-term value, with nearly one in five describing themselves as “very concerned” about overinvestment.
Zwick argues that this internal tension is actually a positive signal for the industry. In the early stages of any major technology cycle, unchecked enthusiasm often leads to wasteful spending.
Today’s finance leaders, however, are taking a more disciplined approach — spending aggressively while subjecting every investment to rigorous scrutiny.
“Finance is writing the checks and worrying about them at the same time,” Zwick noted. “In the receivables data we see across the market, that skepticism is what makes the spending disciplined enough to deliver returns.”
According to Billtrust’s data, 79% of organizations already using AI in finance are reporting tangible returns, including reductions in Days Sales Outstanding (DSO) and faster cash application. These results are particularly notable given that many of these AI deployments have only been operating at scale for 18 months or less.
Zwick emphasized that the conversation has moved beyond whether to adopt AI. With 84% of finance teams already leveraging the technology in decision-making, the focus has shifted to optimizing deployments, scaling successes, and identifying new high-impact use cases.
The pressure to invest is compounded by current market realities. More than two-thirds of customers are paying slower than they were six months ago, and 34% of finance organizations have already reduced headcount, leaving remaining teams to manage heavier workloads with tighter margins.
“The companies that will win are the ones weaving AI into the fabric of how their finance teams already work,” Zwick explained. “The accounts receivable professional at a lumber company in Ohio shouldn’t have to understand machine learning to benefit from it.
She should just notice that cash is arriving faster, disputes are resolving sooner, and her workload has gotten lighter.”
Disciplined AI Investment: Key Traits of High Performers
Zwick outlined several characteristics shared by organizations seeing strong results from AI:
-Every investment is tied directly to measurable cash outcomes such as DSO, working capital improvement, or fraud reduction.
-Deployment timelines are kept short with frequent reassessments — 78% of finance teams now revisit forecasts quarterly.
-Successful implementations involve true process redesign rather than simple bolt-on technology.
-Investment in defensive AI applications, such as fraud detection and deepfake defense, is rising rapidly alongside automation tools.
As CFO of Billtrust, Zwick believes the finance leaders who will thrive in this environment are those who balance bold investment with analytical rigour.
“The CFOs who are only spending are going to get burned,” he said. “The ones who are only worrying are going to get left behind. Those that take a tactical and analytical approach to AI spend will thrive.”
