A generation of fintechs, spanning Ramp, Brex, Bill, Navan, Airbase, and dozens more, have spent the past handful of years pouring machine intelligence into the guts of spend management. The result? AP workflows that once required armies of clerks have, for many firms, become nearly touchless.
Thanks to advances in automation and artificial intelligence (AI), as well as API-driven integrations, vendor onboarding, invoice ingestion, spend categorization, anomaly detection, and payment timing have all become automated or at least semi-autonomous, at least as it relates to the spear-tip of the marketplace. AI didn’t just make AP faster; it redefined the expectations of speed and control across the finance function’s edge cases.
But accounts receivable (AR), the natural counterweight to AP, has not enjoyed the same transformation. AR remains the land of spreadsheets, inbox triage, and the perennial hope that a customer’s “just circling back” email means a check is actually coming. While AP has sprinted into an AI-first future, AR is still negotiating with the past. For operations leaders trying to compress their Time to Cash™ cycles, this imbalance is becoming potentially untenable.
The uncertainty surrounding Time to Cash, however, has rarely been about unwillingness to pay. It has traditionally been about informational friction. Forward thinking CFOs are starting to tackle the asymmetry between the intelligence of the AP side of a transaction and the relatively rudimentary processes on the AR side. AI, it is turning out, could one day collapse that friction by connecting AP and AR directly.
See also: Why CFOs Who Prioritize Cash Flow Improvements Start With Receivables Innovation
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AP Has Been the Launchpad, Not the Final Destination
To understand why the connection between AP and AR in a future commerce landscape may matter more than the individual components, it helps to examine AP’s trajectory. AP has been flooded with innovation because the domain is structured by nature. Every company has invoices, purchase orders, and rules about how spend should flow. This lends itself well to automation.
Over the last decade, fintech companies layered OCR, categorization algorithms, smart approval chains, anomaly detection, and behavioral analytics on top of historically fragmented workflows. AP systems became more predictable, more compliant, and more autonomous.
While AP was enjoying a wave of automation, AR remained stubbornly manual. PYMNTS Intelligence, in collaboration with FIS research, estimates that operational inefficiencies tied to reconciliation cost institutions roughly $98.5 million annually, largely because manual work remains embedded in billing and data collection workflows.
This human-heavy dynamic persists even as the rest of the enterprise moves toward autonomy. AR systems typically organize work but do not execute it. They surface insights but do not negotiate or resolve. They track aging but do not predict payment intent with precision.
What has changed today is the water level of AP readiness. AP is now digitally mature enough and structured enough for something new to plug into it. And that “something” might be AR’s long-overdue transformation.
“We think the supplier perspective on acceptance strategy has evolved quite a bit,” Billtrust Senior Vice President, Payments, Kunal Patel told PYMNTS in an interview posted Monday (Dec. 8). “The inflection point a few years ago was suppliers or merchants deciding that they need to stand up a payment acceptance policy that is more aligned or reflective of their business objectives.”
Read more: Optionality Puts AR in the Driver’s Seat of B2B Payment Behavior
When AP and AR Talk, Time-to-Cash Can Compress Dramatically
AR isn’t the last frontier in finance because it’s ignored. It’s the last frontier because it’s challenging and comparatively unstructured. But AI is finally becoming capable of handling the nuance.
According to the PYMNTS Intelligence report “Time to Cash™: A New Measure of Business Resilience,” 83.3% of surveyed CFOs are planning to use at least one AI tool to help with cash flow cycle improvements.
“The way in which you pay and get paid … is now in and of itself a really important strategic element in your business,” Boost Payment Solutions founder and CEO Dean M. Leavitt told PYMNTS in an interview last month.
The real unlock is not that AR is becoming more autonomous, or that AP is now API-driven. It’s that each function now possesses enough structure, intelligence and machine reasoning to potentially collaborate directly.
Leaders across the next corporate finance era could be the ones that treat AP and AR not as two sides of a ledger but as two intelligent systems capable of interacting in real time.
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