4 Ways AI Adds Value to AR Automation

Artificial intelligence (AI) creates value across all areas of business. Accounts receivable (AR) is no exception. In fact, half (50%) of finance leaders anticipate using AI to automate their repetitive AR tasks, and 41% expect to use it to support strategic decision-making. 

That’s what the results from our 2026 Cash Flow Clarity Report show—demonstrating that finance leaders recognize the value AI can play in their receivables functions. 

Whether you’re enhancing a mature AR automation environment or you’re in the early stages of creating one, consider the benefits AI can deliver around restoring cash flow confidence, predicting payment behaviors, and enhancing decision-making through clearer strategic foresight.

Even as accounts receivable teams prioritize AR automation, cash flow uncertainty is still a reality. According to our report, 78% of finance leaders say unexpected accounts receivable issues force adjustments to strategic decisions such as capital investment, hiring plans, or borrowing. 

AI is another tool accounts receivable teams can turn to in their efforts to restore cash flow certainty—providing predictive insights that allow them to respond more quickly and anticipate risk even earlier in the receivables cycle, unlocking time savings that free up more resources for strategic work. 

Achieving this mature state means integrating AI with AR automation, and letting the two work seamlessly together in a single environment that draws on the benefits of both. 

Doing so can turn receivables into a strategic advantage, creating more certainty and enabling faster, more confident choices around investments, borrowing, and resource allocation.

If your accounts receivable team is looking for ways to benefit from AI, the following are four areas to start (or objectives to pursue). By applying AI to these areas, you can maximize its impact within your AR automation environment.

Our data shows that 79% of finance leaders lose confidence in cash flow forecasts when they stretch beyond 60 days. At that point, planning becomes constrained: working capital flexibility tightens, investment decisions slow, and exposure to further payment delays increases. 

The longer that uncertainty persists, the harder it becomes to regain control.

That makes it more important than ever to build confidence in your cash flow and anticipate risk earlier in the receivables cycle. You can do this by accessing strategic insights that can help you better understand payment patterns and proactively act on them. 

AI and machine learning capabilities help do that, enhancing forecasting capabilities by analyzing past payment patterns in order to predict which customers are likely to pay and when. Through these predictive insights, finance teams can forecast more clearly and focus their collections efforts on the accounts that matter most or are more likely to pay—building more predictable cash flow as a result. 

Applying AI earlier in the collections lifecycle also allows you to preemptively segment high- and low-risk customers based on past payment behaviors. By customizing your communications approach and dunning notifications this way—using personalized workflows based on urgency, risk, or relationship—you can optimize payments and enhance confidence in cash flow.

Today, 55% of finance leaders are seeing requests for longer payment terms, and 53% say customers are asking for payment plans more frequently. Payment behaviors like these have made cash flow less predictable. That lack of predictability, in turn, can impact decision-making. 

That’s consistent with our findings, where 78% of finance leaders say unexpected accounts receivable issues are forcing adjustments to strategic decisions like capital investments, hiring plans, or borrowing. 

To meet the needs of these changing customer payment behaviors, accounts receivable teams must move from reactive execution to proactive leadership. Many are turning to AI as a means to do so, with 2 out of 5 finance leaders (41%) expecting to use AI to support their strategic decision-making. 

Through clearer cash flow forecasts and tools like predictive analytics, AI provides the foresight and risk assessment capabilities teams need to strengthen their financial resilience, restore control over their receivables cycle, and empower stronger long-term planning.

With 74% of finance teams devoting a meaningful amount of time every week to chasing late payments, there’s often little time left for higher-value strategic work like forecasting, analysis, and strategic planning. Repetitive, manual tasks like invoicing, reconciling payments, and following up on late payments often take precedence, but these operational inefficiencies can drain cash flow and strain your team's capacity.

By implementing AR automation, teams are able to reduce many of these mundane but critical tasks: from generating invoices to sending automatic reminders and dunning notifications to collecting late payments. But AI adds another layer of efficiency, taking on tasks like: 

• Cash application: AI and machine learning tools can read digital or paper transactions, including wire transfers, ACH, and checks, to accurately reconcile payments with open invoices without the need for manual intervention. These built-in capabilities get smarter with each transaction, reducing the chance of errors and ensuring nothing gets missed.
• Collections workflows: Machine learning and AI can analyze past behavior patterns and prioritize accounts for collections based on the largest opportunities and by predicting which customers are likely to pay and when. AI can also be used to generate and automate follow-ups to save your collections team time chasing past-due payments.

Almost half (47%) of finance leaders anticipate implementing AI to improve efficiency. But this can come in multiple forms. In addition to automating manual tasks, as we saw above, AI can also help add intelligence and foresight to the strategic planning process, creating strategic as well as operational time savings. 

By analyzing payment trends—whether their customers are paying on time, for example, or asking for alternative payment plans—finance teams can use AI to better assess their payment options and credit policies to determine how to improve confidence in their cash flow. 

The strategic value AI offers helps save time by: 

• Identifying payment risks earlier
• Prioritizing collections activities
• Producing more reliable cash flow forecasts 

This allows finance teams to better understand their risks and opportunities in less time, helping them make decisions faster. It also makes it easier for these teams to shift their policies as needed—changing their payment options or approach to credit, for example, as payment behaviors evolve—helping them stay agile.

In just a few short years, AI has become a useful and reliable tool for finance, including accounts receivable. And it has a strong role to play in AR automation, with the potential to help teams achieve sustained predictability and greater confidence in their cash flow. 

Versapay’s AI and machine learning tools—including AI-enabled cash application software and collections automation software—complement our AR automation solutions. They help provide a cohesive end-to-end environment that builds efficiencies into every step of your accounts receivable process, increasing confidence in cash flow and helping you make more time for strategic work.