AI Agents

AI Agents for AR: Automate and Accelerate Collection

Accounts receivable is one of the most critical yet under-automated functions in finance. This post explores how AI agents bring speed, structure, and control to the collections process without changing your existing systems

July 3, 2025

AI Agents for AR: Automate and Accelerate Collection

Accounts receivable isn’t broken because of one big problem—it’s broken because of a hundred small ones that pile up every week. In the U.S., 55% of all B2B invoiced sales are overdue—a figure that underscores the systemic nature of the issue.

Teams are relying on spreadsheets, calendar reminders, and email templates to recover what the business has already earned. Collections become a game of catch-up—inefficient at best, damaging at worst.

Yet, while AR execution is stuck in the past, the rest of the finance team has been moving forward for years. FP&A is automating forecasting. Accounting teams are streamlining close with reconciliation bots. Treasury is turning idle cash into strategic reserves. AR is the last high-friction frontier, and it’s ripe for reinvention.

Enter AI agents: autonomous software teammates that don’t just track collections—they do the work. Agents don’t just track what’s overdue—they bring structure and intelligence to the entire AR aging workflow. They surface the most significant risks, flag disputes stuck in limbo, and prioritize where to intervene. With visibility into your ledger, payment behavior, and risk patterns, agents help finance teams stay ahead of problems rather than react to them.

This isn’t about replacing teams. It’s about upgrading execution. The companies that adopt agents now won’t just collect faster—they’ll collect smarter, with less leakage, fewer errors, and absolute control over cash.

The future of AR isn’t more tools. It’s autonomous workflows. AI agents make that possible.

Disputes, Delays, and Disconnection

Accounts receivable have always been the lifeblood of a business. It may not get the spotlight, but it keeps the business running. When AR slows down, cash dries up. And yet, the processes behind collections remain stuck in the past, built for a simpler, less fragmented world.

Today’s reality is far messier. Consider something as basic as a purchase order dispute. Nearly half of all AR disputes stem from incorrect or missing PO information. These are avoidable issues, but they persist because teams are working across disconnected systems, reconciling mismatched data by hand, and lacking real-time visibility into what’s wrong, where, and why.

The impact goes far beyond delayed payments. It’s a drain on people. Over a quarter of AR professionals report spending between 25% and 50% of their day resolving disputes. Most businesses still manage those disputes manually, often via email or spreadsheets. The result is slow response times, higher error rates, and strained customer relationships.

Staying up to date is another key struggle. According to recent surveys, 77% of AR teams say they aren’t up to date. That means stale aging reports, inconsistent follow-ups, and murky visibility into cash positions. Finance leaders are making working capital decisions based on outdated information and getting caught off guard when collections fall behind schedule.

The pattern is clear: these aren’t execution failures. They’re infrastructure failures and part of a broader systems problem we explored in AI Agents in Finance. AR still runs on brittle systems, manual effort, and workflows that weren’t built to scale. It’s no surprise that even the most diligent teams feel underwater.

Graphic showing average Days Sales Outstanding (DSO) by industry. Retail has the lowest DSO at 5 days. SaaS averages 38 days, healthcare 47 days, manufacturing 39 days, wholesale 40 days, and business services 41 days. Data sourced from Stripe and Forbes.

DSO naturally varies by industry. Retail operates with a tight 5-day cycle, whereas healthcare sits around 47 days. SaaS, manufacturing, wholesale, and business services all hover around the 38–41 day mark. That variability is expected—different models, different timelines. But it’s not something finance teams have to accept passively. According to Forbes, SaaS companies have reduced their average DSO from 58.7 days in 2020 to 54.03 days in 2024 by leveraging automation and AI-driven workflows. It’s a clear signal: with more intelligent systems in place, every industry has room to move faster on collections—and turn cash sooner.

This is where AI agents like Concourse step in. Instead of adding another dashboard or layer of oversight, they embed directly into your existing AR workflows—automating follow-ups, surfacing risks, and resolving issues before they stall payments. By removing the friction that slows collections, agents help teams accelerate cash flow without adding headcount. In today’s environment, where liquidity can’t wait, that kind of execution speed isn’t just nice to have—it’s a competitive advantage.

AI Agents Explained: Smarter AR Execution Without Rebuilding Systems

AI agents are a new kind of software teammate—built to support AR workflows with speed, structure, and precision. They’re not dashboards, and they’re not just basic automation. They’re intelligent operators that plug into your systems and help your team take action, faster and with less manual effort.

Here’s how it works. The agent connects to your ERP and billing systems, pulling real-time data on open invoices, aging balances, payment patterns, and dispute status. When prompted, it analyzes that data to surface overdue balances, flag high-risk accounts, and highlight areas where follow-up is most urgent.

Do you need to know which customers are trending late? Or how much exposure sits in the 61–90 day bucket? Just ask. The agent returns clear, contextual answers in seconds, ready for review, escalation, or action.

There’s no reimplementation required. Agents sit on top of your existing tools and respond to plain-language prompts—no workflows to rebuild, no new systems to learn. That simplicity makes the shift from reactive to strategic not only possible, but fast.

Because in most finance teams, AR execution still feels like a grind. Even with decent systems in place, collections remain manual, involving tasks such as reviewing aging reports, flagging risks, drafting follow-ups, and communicating with account managers. It’s reactive by nature, and the burden falls on individuals.

AI agents offer a different way of working. Instead of just tracking what's overdue, they help your team prioritize where to intervene. Instead of managing backlog, you manage outcomes. You decide what needs a human touch—everything else is prepped, analyzed, and ready to go.

The result is a more responsive, less chaotic AR function. Risk declines. Effort scales. And your team gains the clarity and control needed to protect cash and support the business without burning out.

What Agents Can Do

AI agents don’t just automate reminders—they generate the kind of real-time insights and structured outputs that finance leaders can use immediately. From reconciliation to forecasting inputs, these prompts demonstrate how agents transform AR into a proactive, data-driven function.

Aging Summary for Strategic Review

Summarize total AR by aging bucket and highlight the top 10 customers in the 61–90 day category.

→ The agent pulls live AR data, organizes it by standard aging brackets, and surfaces the highest exposures nearing risk thresholds. The output includes customer names, invoice counts, and total balances, giving you an at-a-glance view of where to intervene.

Dispute Exposure Quantification

What is the total AR value currently tied up in unresolved disputes over 10 days old?

→ The agent reviews dispute status logs across systems, aggregates the amounts held up by issue type or customer, and highlights aging patterns—helping you quantify leakage and escalate resolution where needed.

Forecast Accuracy by Segment

Compare forecasted AR collections to actuals for the past 30 days by customer tier.

→ The agent matches projected inflows with bank-verified payments, calculates variance by segment, and identifies where assumptions broke down—so forecast logic can be corrected before the next cycle.

Risk-Weighted Exposure View

Group open AR by customer risk score and show total balance in each risk tier.

→ The agent assigns risk profiles based on payment history and credit behavior, then aggregates outstanding balances into low, medium, and high-risk tiers, equipping you to focus collections where it matters most.

GL Reconciliation and Variance Flagging

Reconcile AR subledger with the general ledger and flag any discrepancies over $1,000.

→ The agent compares detailed entries, identifies mismatches, and tags root causes, such as timing differences or missing transactions, delivering a clean exception report for close review.

With these kinds of prompts, AI agents shift AR from a reactive cycle to a performance layer that feeds directly into forecasting, cash planning, and reporting. It’s not just faster work—it’s better answers for the decisions that matter most.

The Bigger Outcome – From Reactive to Strategic

There are few things more frustrating in finance than knowing what needs to be done, and not having the time or systems to do it well. That’s the reality of AR. Everyone agrees it’s essential. Everyone understands it impacts cash. But no one wants to spend their day chasing overdue invoices, resolving disputes, or updating status logs.

AR is one of those nagging workflows that hides in plain sight. It’s rarely urgent until it’s a problem. And by the time it shows up in the forecast or the board deck, it’s already too late. Late collections turn into missed targets. Unresolved disputes turn into revenue gaps. And a few “small” issues quietly compound into real risk.

That’s why automating AR matters more than most people think. It’s not just about efficiency—it’s about elevating the function from background noise to a core part of financial performance.

With AI agents, AR stops being a backlog of to-dos and becomes a real-time system for managing outcomes. The agent handles the routine work in the background—tracking aging, escalating risk, surfacing disputes—so your team can stay focused on review and decision-making. You’re not just collecting cash. You’re directing a process that supports liquidity, strengthens forecasting, and gives the business confidence in the numbers.

And that changes the role of AR from reactive support to strategic infrastructure. It becomes a lever for financial control, not just a box to check at month-end. When execution runs independently, the team gets to lead, not just follow up.

Why Concourse

Concourse builds AI agents specifically for corporate finance teams, designed to handle the friction-filled work that slows you down. Our agents automate accounts receivable from end to end, tracking aging, surfacing risks, flagging disputes, and reconciling balances—without requiring you to lift a finger.

They plug directly into your ERP, CRM, and billing systems. No reimplementation. No retraining. Just faster execution and clearer visibility from day one.

If you’re ready to stop chasing AR and start commanding it, join the waitlist or reach out to hello@concourse.co to get started.

FAQ – AI Agents for AR with Concourse

How can AI agents improve accounts receivable collections?

AI agents like Concourse streamline AR by identifying high-risk accounts, and escalating disputes—reducing manual workload and accelerating cash collection.

What makes Concourse different from traditional AR automation tools?

Unlike basic automation or dashboards, Concourse agents plug directly into your ERP and CRM, and provide contextual insights—no new systems to learn, no workflows to rebuild.

How do AI agents handle AR disputes?

Concourse agents identify unresolved disputes, quantify the value tied up, and escalate aging issues—so your team can prioritize resolution and reduce payment delays.

Can Concourse integrate with our existing billing and ERP systems?

Yes. Concourse connects directly to your existing ERP, billing, and CRM systems with no reimplementation required, enabling seamless data sync and real-time execution.

What types of AR tasks can be fully automated by Concourse agents?

Concourse automates aging analysis, risk scoring, dispute flagging, and reconciliation—allowing teams to focus on strategic decisions instead of repetitive tasks.

How does Concourse help reduce DSO (Days Sales Outstanding)?

By providing teams with the ability to identify late payers and surface risk-weighted exposures instantly, Concourse helps companies accelerate collections and reduce DSO across customer segments.

How do AI agents determine which invoices are most at risk?

Concourse analyzes payment behavior, dispute history, and customer risk profiles to highlight high-risk invoices and prioritize follow-up where it matters most.

Is it possible to track AR performance in real time with Concourse?

Absolutely. Concourse provides real-time summaries, variance analysis, and risk-based aging views—helping finance teams monitor AR health and inform cash planning instantly.

What’s the ROI of using AI agents for AR compared to hiring more staff?

Concourse delivers scalable execution without adding headcount. It reduces manual effort, speeds up collections, and improves forecasting accuracy—delivering measurable ROI faster than traditional hiring.

Can AI agents like Concourse help with AR forecasting?

Yes. Concourse agents compare forecasted vs. actual collections, identify breakdowns by customer tier, and feed more accurate inputs into your forecasting models.

Can Concourse agents support broader finance workflows beyond AR?

Absolutely. While this post focuses on accounts receivable, Concourse supports a comprehensive suite of finance workflows, including FP&A, treasury, accounting, and audit. Whether it’s reconciling entries, refreshing forecasts, or generating variance analysis, Concourse agents are built to execute—not just analyze—across the entire finance stack.