In an era where liquidity defines corporate survival, the back office has become a strategic battleground.
The unglamorous accounts receivable (AR) function, once considered a cost center, is at the heart of this transformation. AR had been synonymous with manual invoices, aging spreadsheets, and overdue notices. But now, a wave of automation, data intelligence, and artificial intelligence (AI) is recasting it as a command center for cash flow, customer experience, and financial foresight.
But despite the proliferation of FinTech tools and digitization promises, most companies still struggle with the basics of AR. According to PYMNTS Intelligence data from the “June 2025 B2B and Digital Payments Tracker® Series” report “From Friction to Flow: AR Automation in 2025,” 83% of firms have yet to fully automate their AR operations.
In practice, this means invoices routinely go out late, payment terms are poorly enforced, and collections remain reactive — conducted over email or phone in many small and mid-sized businesses.
The consequences are anything but trivial. For middle-market firms, delayed payments result in an average of $19 million in lost revenue annually. Nearly 30% of invoices go unpaid every month. This is more than five times the typical rate in healthy financial ecosystems.
This is not just a back-office inefficiency. It’s a systemic liquidity problem that can hamper working capital, stress customer relationships, and distort forecasting.
Cost of Invoice Friction
In the age of predictive AR, where CFOs are no longer just chasing checks but anticipating behavior, modeling risk and accelerating growth, manual processes can act less like a speed bump and more like a sinkhole.
In response, finance leaders are building a new kind of playbook — one that replaces fragmented, labor-intensive processes with automation and real-time data. The goal? To shift AR from a transactional workflow into a predictive, strategic asset.
The first step is eliminating manual choke points. Tools now exist that automate invoice generation, digital delivery, payment tracking, dispute resolution, and reconciliation — all within integrated enterprise resource planning (ERP) or finance platforms. When executed well, this creates a continuous, touchless AR pipeline.
According to the PYMNTS report, companies that adopt these systems can reduce their days sales outstanding (DSO) by 15% to 25%, potentially translating into millions in unlocked working capital.
Once workflows are digitized, they become data-rich. This is where AI comes in, by analyzing payment patterns, identifying at-risk accounts, and modeling cash inflows based on behavioral history rather than static terms.
These insights can feed directly into dynamic cash forecasting, enabling CFOs to model different liquidity scenarios and plan funding needs with greater accuracy. In volatile markets, this may help to make the difference between defensive downsizing and proactive investment.
Read the report: From Friction to Flow: AR Automation in 2025
The final frontier in AR transformation is not just collecting faster, but collecting smarter. Virtual cards and embedded finance, where payment rails are integrated directly into the invoice or procurement workflow, accelerate the adoption of payments innovation across the AR function by offering effective solutions.
With virtual cards, customers can pay instantly while earning rebates or managing internal cash cycles. For suppliers, it means faster cash flow and reduced risk. Embedded payment experiences, much like “one-click” checkout in eCommerce, are now making their way into B2B transactions.
This frictionless payment architecture also enhances customer experience. Instead of being hounded for overdue payments, buyers are nudged with intelligent reminders, dispute resolution options, and flexible financing embedded into their AR portals.
As macroeconomic pressures from inflation to interest rate volatility mount, the CFO’s role continues to evolve. In this environment, predictive AR becomes more than a tool. It’s a competitive differentiator.
By 2027, industry analysts project that over half of all AR processes in mid-to-large enterprises will be augmented by AI and machine learning. This will shift AR from a back-office function to an intelligence hub; one that informs pricing, sales strategy, customer targeting, and capital allocation.
The result? A finance function that doesn’t just count the money but multiplies its potential.
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