The Forgotten Stage of Q2C in 2026: Why Ignoring AR Will Cost You More Than You Think

Over the last decade, Quote-to-Cash (Q2C) modernization has followed a clear pattern: invest where certainty is contractual and auditable. For example: investing in pricing engines, contract, billing, and revenue systems made sense as it helped formalize rules, enforce terms, produce accuracy, and protect compliance respectively.

Pricing engines formalize rules. Accounts Receivable (AR) - by contrast - lives downstream of all four; where outcomes are shaped less by policy and more by payer behavior. Customers delay payments for reasons contracts never anticipated. Disputes arise after invoices are technically “correct.” Promises-to-Pay (P2Ps) sit in inboxes, not systems. So; AR was implicitly categorized as operational, not strategic. AR didn’t get deprioritized by accident. It was designed out of the transformation agenda.

A PYMNTS study surveying 100 U.S.-based CFOs found that, despite years of finance digitization, Accounts Receivable automation remains “broadly overlooked.” Only 27% of firms had automated even half of their AR processes, and 70% reported using no specialized AR automation at all in the prior six months.

At the same time, the operational consequences are visible at scale. Atradius’ 2025 U.S. B2B Payment Practices Report shows that 43% of B2B invoices are overdue, with overdue invoices converted to cash 20 days past due on average. The most commonly cited cause? Administrative inefficiencies in payment processes; not customer insolvency, not pricing errors. This is what a structurally under-instrumented AR layer looks like in aggregate.

‍

Why strong upstream Q2C does not protect you downstream

As a finance leader, you may still be operating under a quiet belief: if pricing, contracts, and billing are sound, AR performance will normalize. It doesn’t however because AR is not a continuation of upstream certainty. It’s a translation layer between internal correctness and external behavior.

A perfect invoice does not ensure that:

• It reached the right payer
• It survived the customer’s internal approval workflow
• It avoided a downstream dispute
• It aligned with how the customer actually remits

When AR is left to reconcile these realities manually across ERP aging, email threads, bank files, and spreadsheets; the system may reconcile balances, but it can’t govern outcomes.

‍

What doing nothing on AR, actually costs

Consider a typical $500M B2B organization. According to the Atradius’ 2024 U.S. B2B Payment Practices Report, 60% is sold on credit. This translates to $300M in receivables. A standard 15-day gap in the DSO can have a huge impact.

• A 15-day excess DSO on $300M of credit sales ties up roughly $12.3M in cash at any point in time. That money is not idle by choice. It is either covered by short-term borrowing or offset by holding more liquidity elsewhere. At a 6% cost of capital, that delay translates into ~$740K per year in financing or opportunity cost; before anything goes wrong. This is the baseline penalty for tolerating AR delay.
• Industry benchmarks show that roughly 8% of B2B invoices are written off as bad debt. In our example, $300M × 8% = $24M in annual bad debt exposure. Not all of that is preventable. But even assuming only 25% is execution-related (disputes that linger, follow-ups that decay, documentation that arrives too late), that’s still $6M a year in permanently lost revenue. Let that sink in.
• Since AR cash is unreliable, most companies end up borrowing against their own receivables. Even if only half of the trapped $12.3M requires external financing, that translates to ~$6.15M × 6% = ~$370K per year
• Labor costs grow quietly and inefficiently. In under-tooled AR environments, work scales linearly through manual follow-ups, email-based dispute handling, human cash application exceptions. Assuming that the business has 10 AR FTEs at $60K cost, and where ~30% of time is spent on low-leverage, manual work; that’s ~$300K annually in labor cost that does not materially improve outcomes. That’s a sizable proportion of your operational costs.
• Even a 1% excess liquidity buffer on $500M revenue equals $5M sitting idle. At a modest 5% opportunity cost, that’s $250K per year in foregone return or deferred investment.

When you aggregate only the defensible, directly quantifiable impacts, the visible annual cost of doing nothing = ~$7.7M per year. And this does not include revenue concessions buried in dispute settlements, customer churn driven by AR friction, sales, legal, and executive time pulled into escalations, audit and compliance remediation from poor AR traceability, shadow systems built to compensate for missing tools, or non-linear risk amplification during downturns

In other words, $7.7M is the visible cost floor; not the ceiling. You’re leaving more money on the table than just outstanding payments.

‍

The “AR reframe” finance leaders need to make

When AR is excluded from serious budgeting, you aren’t choosing efficiency. You are choosing to absorb recurring, compounding financial leakage instead.

That leakage:

• Is large enough to matter
• Predictable enough to model
• Avoidable enough to challenge

This leaves AR under-instrumented and you may need to accept measurable financial loss. Once you see AR in these terms, as a capital discipline problem, not a collections workflow issue: it stops competing with discretionary tooling.

You need to start repositioning AR in the financial stack, and AR needs to get treated as a decision layer, which provides behavioral intelligence and cash governance. With AI and advanced analytics, AR use cases like collections prioritization, payment forecasting, dispute management, and cash applications can change outcomes with context instead of hindsight.

‍

Q2C Breaks Where Cash Stops Being Governed

For years, Q2C optimization has focused on what can be made deterministic: pricing, contracts, billing, revenue recognition. That focus delivered control upstream. It did not deliver predictability downstream.

Accounts Receivable sits where internal correctness meets external behavior. When AR is under-instrumented, organizations lose the ability to see cash risk early, intervene with intent, and explain outcomes with confidence. The result is not a broken process, but a steady accumulation of tolerance: delayed cash, quiet revenue concessions, defensive liquidity, and senior time lost to escalation.

This is why Q2C does not fail at the quote or the invoice. It fails at the point where cash should become governed rather than explained.

Optimizing Q2C is not about making upstream systems more perfect. It is about ensuring intelligence, accountability, and decision-making persist through the final mile. That requires treating AR not as a collections function, but as a decision layer in the financial stack.