The inevitable shift to digital payments for business-to-business (B2B) transactions continues, with each year seeing fewer organizations sending out paper checks to cover their costs. One of the key drivers for this trend is the overall convenience it delivers to not only buyers but also beleaguered accounts receivable (A/R) departments, which are expected to provide faster, more accurate payment cycles in the face of growing workloads and regulatory burdens.
To address the demand for ever-increasing efficiency, many organizations have begun incorporating artificial intelligence (AI) into their payments and accounts receivable (A/R) efforts. In this article, we’ll take a look at this emerging technology as well as the potential impacts it may have on your billing and invoicing efforts.
What is AI in accounts receivable?
The actual use cases for artificial intelligence in accounts receivable (A/R) processes are rather broad, but they typically align with one of two primary focuses: pattern recognition or automation. For pattern recognition — particularly identifying trends too subtle to be noticed by the human eye — this technology lends itself towards improved forecasting through predictive analytics, providing valuable insight to key decision-makers. Similarly, it can be leveraged to detect suspicious or fraudulent behaviors that might impact your payment processes and your bottom line.
In the context of A/R automation, a business might leverage a generative AI tool to streamline the creation of dunning messages or other communications. Alternatively, it can utilize the technology to accelerate rationalization efforts, such as cash application or remittance settlement. Some businesses even rely on AI-powered chatbots to handle simple customer service issues surrounding billing.
How AI can automate accounts receivable processes
Billing
Creating accurate, timely invoices isn’t just a clerical task — it involves synthesizing multiple data streams, including shipping confirmations, sales records, tax rules, and customer profiles. AI can automatically retrieve this information from integrated systems (such as ERPs or CRMs), validate it, and generate invoices without requiring human intervention. This reduces errors, shortens billing cycles, and ensures customers are invoiced as soon as terms allow, helping you get paid faster.
Dunning and Customer Management
Following up on outstanding invoices can be tedious and inconsistent when done manually. AI-driven dunning automation enables businesses to execute consistent, timely, and even personalized follow-ups based on customer behavior and payment history. With generative AI, these reminders can be customized for tone and timing — automatically escalating messages when necessary or adjusting frequency based on response data. This makes it easier to maintain customer relationships while still enforcing payment discipline.
Cash Application and Reconciliation
Matching incoming payments with the correct invoices can be one of the most time-consuming aspects of accounts receivable (A/R), especially when remittance information is unclear, payments span multiple invoices, or customers pay in bulk. AI can rapidly parse transaction data, remittance notes, and historical patterns to auto-match payments with open invoices, reducing the need for manual oversight. This helps eliminate reconciliation bottlenecks, even as your transaction volume grows.
Reporting and Support
AI can also simplify reporting and internal support by consolidating accounts receivable (A/R) data into dashboards, generating forecasts, and identifying trends in late payments or cash flow risk. Rather than relying on static reports or manual analysis, finance teams can access real-time insights and proactive alerts. AI can even surface anomalies or suggest actions, such as flagging accounts that are trending toward delinquency or recommending changes to credit terms.
Risk Management
Credit decisions are often based on static rules or outdated information. AI can ingest and analyze massive datasets, like past payment behavior, industry risk, and third-party credit reports, to help you assess a customer’s likelihood of timely payment. This enables smarter decisions on who to extend credit to, under what terms, and when to escalate accounts for collection — all in real-time.
AI technologies that power accounts receivable automation
Put simply, AI refers to any system or solution that can automate tasks that typically require human intelligence to complete. But the actual component technologies used to achieve this goal will vary depending on the platform, with some of the most common including:
- Machine learning (ML): incorporates complex algorithms that can detect patterns within raw data, make decisions based on this analysis, and improve the performance of these decisions over time without additional programming
- Natural language processing: pulls relevant details from unstructured data (e.g., emails, chat logs, journal entries), converting it into actionable intelligence
- Predictive analytics: focuses on forecasting future events based on known historical data
- Robotic process automation (RPA): automates repetitive tasks, performing them in compliance with established guidelines
Benefits of AI in accounts receivable
As businesses — and their executive leadership — continue to seek opportunities to streamline the entire procure-to-pay process for their customers, AI has been increasingly adopted by financial departments worldwide. In fact, according to data compiled by PYMNTS, chief financial officers (CFOs) among surveyed mid-market businesses are expecting to increase their investment in AI by 78% over the course of 2025.
Some of the strongest arguments for why CFOs are using AI in accounts receivable are that it:
Accelerates processes
AI makes it easy to automate your entire invoice-to-cash (I2C) process, delivering streamlined workflows that let you complete core tasks in seconds that might take minutes or hours to do manually. Further, AI-driven decision engines allow you to keep processes moving smoothly without the direct intervention of staff, meaning your billing doesn’t stop when the workday does.
Promotes accuracy
Repetitive, mundane, and manual tasks create numerous opportunities for human error. But when these touches are handled by AI, you can be much more confident that the right data is being captured, stored, retrieved, and used in your invoices, financial records, and external reports. At the same time, AI-powered cash application means that when payments come in, they’ll be properly routed to corresponding customer accounts, avoiding irate customers and other potential headaches.
Stabilizes cash flow
With faster processes and fewer errors, you’ll be regularly converting your invoices into usable cash, letting you maintain day-to-day operations while offering more flexibility to capitalize on current opportunities or plan for the future. And when AI is driving your forecasting, those plans are much more likely to align with eventual outcomes.
Hardens security
With the pattern-recognition capabilities of AI tracking your overall payment processes, you’ll be able to identify and react to potential fraud more quickly. These solutions are ideal for identifying duplicate invoices, unauthorized shipments, and other shenanigans.
Augments decision-making
The success of any plan you put in place, any improvement you pursue, and any change you want to enact is limited by the information you have in hand. If you’re using stale, outdated data to drive your business, expect problems. But when AI is actively mining through your records in real time, uncovering sales trends and detecting hidden relationships between dunning and payment timelines, you’ll be in a much better position to make wise choices, identify problem areas, and vet the value of process changes.
The future of AI-powered A/R automation
While AI has proven highly effective at automating routine, rules-based AR tasks, complex billing scenarios, and process exceptions still present challenges that often require human judgment. However, as AI models continue to evolve, learning from larger, more diverse datasets, they’re expected to handle increasingly nuanced situations with minimal human intervention. This shift will allow finance teams to focus more on strategic initiatives rather than transactional oversight.
Much of the innovation in this space will come from more sophisticated predictive models. As algorithms are trained on extended historical data and broader behavioral trends, they’ll gain the ability to forecast payment patterns with greater accuracy. In time, these models may even incorporate external variables, such as macroeconomic indicators or policy changes, to identify risks and recommend proactive adjustments to your AR strategy.
We’re also moving toward more personalized and adaptive billing experiences. Soon, AI could generate individualized payment term recommendations based on real-time financial and credit data. Dunning workflows could dynamically adjust tone, timing, and message content based on what’s statistically most effective for each customer, maximizing the likelihood of prompt, full payment while preserving customer goodwill.
Common misconceptions about AI in accounts receivable
As with all technologies, there are some drawbacks or tradeoffs to implementing AI. So, before adding it to your overall architecture — and more specifically, your A/R environment — you should plan ahead and establish clear goals and expectations for your AI journey.
Of course, you don’t want to let any false assumptions regarding the technology color your opinion. Here are some common misconceptions about AI in A/R that we can clear up:
- AI will displace my A/R teams: As it currently stands, even the most advanced AI solutions can’t replace the human element. What they can do, though, is take over repetitive tasks, freeing up your A/R staff to focus on more strategic priorities.
- AI is too expensive unless you’re an enterprise-level company: While deploying your own AI instance can be cost-prohibitive, there are several reasonably priced, AI-powered automation tools already available in the market.
- AI makes it impossible to comply with privacy regulations: Admittedly, exposing your customer and financial data to additional systems — AI or otherwise — creates more opportunities for criminals and data leaks. But with sound governance policies and proactive security and monitoring efforts, you can mitigate this risk and remain aligned with established legal and industry guidelines.
- AI will take over my decision-making: Current platforms let you automate straightforward tasks in compliance with established rule sets, but these efforts still typically require human authorization to be finalized, particularly if financials are involved.
The risks and capabilities of AI will continue to change over the coming years. But with a little consideration and diligence, companies can make smarter, more confident steps toward A/R automation.
Ready to automate your A/R?
AI isn’t replacing finance teams — it’s empowering them. And with our Accounts Receivable Automation solution (powered by the global payment capabilities of Flywire software), we can offload the repetitive, time-consuming tasks of your I2C processes, allowing you and your staff to focus on what’s truly important.
It may be time to evaluate the current state of your A/R processes and schedule a demo with us to explore the potential of what an AI-powered solution can deliver.
