Artificial intelligence has shaken up operations as we know them. Every day, someone is finding a new way to save time on their work by using an AI-powered tool like ChatGPT, Perplexity, Claude, or Gemini.
The world of financial management is no exception. In fact, there are tailored advancements in the field with platforms that use AI to streamline specific workflows. For small and medium-sized businesses (SMBs), these advancements don’t just save time, they’re an advantage over the competition.
In this guide, we’ll cover how AI is reshaping accounts payable, boosting efficiency, and reducing errors in the process. Get familiar with what the technology looks like, how it operates, and how to integrate it into your existing systems.
What is AI in accounts payable?
AI in accounts payable is an umbrella term that refers to using intelligent and adaptive software to automate accounts payable workflows.
Traditionally, accounts payable has been a manual process, especially when there are paper invoices or payments by physical mediums (like checks or cash) that cannot be easily digitized.
But as more processes are moved to software, repetitive administrative tasks like data entry, invoice processing, and document matching can be automated, requiring minimal human input.
Now, accounts payable can be streamlined to a few simple steps, an invaluable add to SMBs trying to maximize the value of the time of its employees.
Types of AI technologies used in accounts payable
Artificial intelligence technologies found in accounts payable software take on a wide array of forms. However, there are four common iterations you’ll find:
- Machine learning (ML): The software learns from historical data and processes to perform the actions an employee would do. For example, it may recognize a specific vendor name to categorize the transaction based on historical categorizations.
- Natural language processing (NLP): Enables the system to digest and interpret data from emails, invoices, and other documents.
- Optical character recognition (OCR): Scans text from printed or digital documents and imports it directly into the system. While not an AI technology in itself, it often uses AI to predict the text if it’s illegible.
- Robotic process automation (RPA): An AI-enhanced, rules-based task automation that follows a set of parameters provided to the system. An example of this in action is forwarding an invoice to a department head for approval based on the content of the invoice.
This list is a sample of how AI is used in accounts payable. The technology in this space is constantly evolving with further advancements designed to save time for finance teams in businesses of all sizes.
How does machine learning and automation work in AP?
The most prominent form of AI in accounts payable is machine learning. This is the technology that adapts to the specific rules and needs of the business.
Machine learning uses algorithms to discover patterns in a dataset. The patterns then inform the automation process.
Specifically in accounts payable, machine learning is trained on invoices, vendor information, transactions, payments, and documents from the past and in the future.
For example, the algorithm may recognize that a recurring invoice from a specific vendor is the business’s usual inventory purchase. Once the invoice is received, it will be categorized as an inventory purchase and forwarded to the appropriate stakeholder for approval.
However, if an invoice is received from the same vendor, for a different amount, outside of the usual window, and without a matching document, it would be flagged for manual review as potential fraud
This is how machine learning saves finance teams time: it takes data about an invoice and turns it into action without manual input. And since the dataset is constantly expanding with new invoices, it’s improving over time.
Examples of AI in accounts payable
To expand on the use cases of AI in accounts payable, let’s look into some specific examples of how workflows will be improved by leveraging this emerging technology.
Automated invoice processing
Accounts payable platforms utilizing AI automatically extract the essential information from invoices for data entry and automate much of the processing workflows.
From a digital PDF or image of an invoice, the vendor information, invoice number, total amount, and individual line items are all captured by the system and matched with supporting documents.
An invoice would only require manual input if it’s illegible, requires clarification, or cannot be matched to a supporting document.
Real-time data analytics and reporting
Given that AI can process invoices as they come in, your reporting and dashboards are always up-to-date without depending on someone’s data entry.
The data in the system is turned into forecasts and analytics that help businesses make better decisions. It may flag costs increasing with a specific vendor or opportunities to get early payment discounts that save money and protect the bottom line.
Predictive analytics
The pattern recognition that powers automation also works in predictive analytics. AI can forecast future costs and invoices based on each vendor’s history with the business, helping you plan your cash flow around upcoming expenses.
Fraud detection
Cybercriminals use invoice fraud to exploit a business for financial gain. It can be done by impersonating a business, submitting fake invoices, and rerouting payments to a personal bank account.
With AI-powered technology, any suspicious activity is flagged to the business to intervene before money changes hands. It will catch if an invoice is outside of the usual cadence, whether there are inconsistencies with vendor or payment information, or if there’s no supporting document like a purchase order.
Seamless integration with the top accounting platforms
By connecting with accounting platforms like QuickBooks, Xero, NetSuite, and more, information is sent and received to confirm accuracy and flag inconsistencies.
This means the AI-powered accounts payable platform doesn’t just revamp your existing AP process; it also improves your overall accounting processes, minimizing workflows and increasing accuracy.
Benefits of AI in accounts payable
Implementing AI in your accounts payable process can have a real impact on your bottom line through these benefits.
Cost reduction and operational efficiency
Manual AP processes are a time sink, and that time costs businesses money. Think about the hourly rate of an accounts payable clerk (estimated to be around $23) and the number of invoices they can process in an hour. If they can process 4-5 invoices in an hour, that’s roughly $5 per invoice based on labor costs alone.
To add to that, there’s the opportunity cost of time being spent on invoice processing that could be used for higher-value work.
If the business is processing a high volume of invoices, the only solution to scaling up operations is to add headcount. But with AI-powered AP, you keep headcount and costs in check.
Improved accuracy and reduced errors
Manual processes are prone to human error, like typos, duplicate entries, and misentered information. These errors require troubleshooting, potentially leading to late payments or missed payments altogether.
With OCR, AI takes information directly from the invoice for input. The manual entry is gone, and so is the chance of human error.
If there’s an error, the system flags it. No more digging for the needle in the haystack, trying to find the invoice causing issues.
Faster processing times
When an AI-backed solution processes an invoice, the workflow starts as soon the invoice is received. And since the work is automated, the process leaps ahead to just the necessary human inputs of reviewing the AI-powered output and processing a payment.
Pair that with an integration that syncs your accounts payable platform with your accounting software, and each task associated with an invoice is expedited from start to finish.
Better fraud protection
The most effective forms of fraud try to mimic use social engineering to try and coerce somebody to make an ill-informed judgment call and send money. But AI doesn’t fall into the same trappings of human emotion.
Pattern recognition and automated matching are likely to catch fraudulent transactions before it’s too late. The real-time alerts ensure that a transaction gets reviewed if it doesn’t look like it belongs.
Data-informed cash flow management
Predictive analytics and forecasting highlight when the business needs the capital to manage large cash outflows. By highlighting these moments before they happen, businesses can pre-emptively plan to have the cash on hand by moving money around or trying to inject immediate sales with a discount or promotion.
Catching a cash shortage before it happens helps SMBs avoid high-cost lending options like invoice factoring or merchant advances.
Automated analytics and insights
Rather than manually compiling reports, spending minutes or hours trying to find the valuable tidbit of information that matters, AI systems update reporting and highlight trends that could impact operations. Finance teams get more data-backed insights and can make quick decisions that save money and time or improve performance.
Stronger supplier relationships
A good relationship with a supplier can go a long way. By quickly processing invoices and turning them into on-time payments, you’re sure to stay in their good books.
Being consistent with your payments opens up the possibility of preferred terms and early-payment discounts. If anything, it’s a great stepping-off point for negotiating the next deal.
Scalability and future-proofing
Implementing AI saves time now, but it only improves as it’s used more. Machine learning is constantly adapting to new information and data, tailoring itself to a business’s operations.
Adopting an AI solution down the line still has value, but each invoice manually processed before you make the switch is an opportunity missed for the platform to get up to speed.
As the business grows, the AI only gets better at completing the work.
Implementing AI in your AP process
Thinking about implementing AI in your operations? Take these five steps to make the move and start reaping the benefits of this emerging tech.
1. Assess your current AP process
Before you commit to a solution, it’s best to know about where your AP process is struggling most. Have conversations with members of the finance team to understand their frustrations and what they’d ideally like to see in a solution.
Also, take note of any special considerations that might make it hard to find an “out of the box” solution. For example, you may work with the same vendor for multiple expense types and need each line item categorized accordingly.
2. Choose your AI-powered AP solution
With the pain points and special considerations, you’re equipped with the info you need to start looking for the right AI-powered AP solution.
Do your own research to start and get internal feedback on the initial options you find. Whittle down that list to a few select options and schedule calls or demos for each so you can see the platform in action and ask any pertinent questions.
3. Set a timeline for implementation
Work with all relevant stakeholders (such as the finance and IT teams) to create a timeline for a phased rollout. Set deadlines for each step so the timeline is adhered to.
Aim for a timeframe where the swap over will cause the least disruption. Look for a period where invoice volume is low to test the new approach with a smaller sample size before the full rollout.
4. Migrate and clean your data
Swapping platforms is a great time to clean up your data, like doing a garage sale before moving. Clean out vendors you may not use anymore and review that all information is up-to-date and standardized.
Having consistent formatting is an integral part of working with AI. Given that it operates on pattern recognition, consistent formatting ensures the information it needs is in the right place for the AI to complete the workflow.
5. Test and adjust
Start by running a few invoices through the system, potentially with one or two vendors you have a good relationship with. Let them know you’re testing a new system and to reach out if they experience issues you wouldn’t otherwise see.
Review the output and adjust the system as necessary. Remember that AI is an adaptive technology that builds off the feedback you provide. Over time, it will learn from your processes and patterns to become a personalized solution for the business.
Best practices for implementing AI in AP processes
To make the smoothest transition to an AI-powered AP solution, follow these best practices and get all of the value with the least disruption.
Choose the right time to make the switch
Switching to a new platform can be daunting, especially to a platform that’s intended to be a hands-off experience.
To give yourself peace of mind and iron out any creases with minimal impact, make the switch when invoice volume is low. If there are any issues with the transition, it will affect the smallest possible volume of invoices, allowing you to refine and adjust before operations ramp up.
Communicate the change to vendors and staff
Everyone who will be impacted by the change should be kept in the loop.
The staff who use the platforms need to know about the change before it happens. Take time to listen to their pain points and find a platform that addresses their concerns. Once the platform is chosen, keep them involved in the implementation process and training.
The vendors who are going to be getting paid need to know in case they’re affected by the switch-over. Letting them know a switch is happening lets them know that a late payment could be from a technical issue rather than ill intent.
Use platform support to get the most out of the software
Part of what you’re paying for with a software subscription is the support team that is there to help their customers make the most of the platform. If you’re not using the support team, you’re not taking advantage of a thing you’ve already paid for.
Whether it’s implementation, making full use of the features, or looking for general best practices, don’t hesitate to reach out to support to get answers directly from the source.
Take the opportunity to make additional changes
When building up from a new foundation, it’s worthwhile to evaluate other aspects of your processes. This is the opportunity to change other things that are connected to the platform you use.
It’s best practice to get feedback from those involved in the accounts payable process to inform what you should look for in a new accounts payable platform. But also take the opportunity to get feedback on other aspects of the work they do.
An efficient accounts payable process requires buy-in from everyone involved. If you’re going to make one change to make the work easier, you may as well look at other parts that can be changed as well.
The future of AI in accounts payable
Everything we’ve discussed so far is about the current state of AI. But the space is ever-changing, and the future is bright with possibilities. These are just a few examples of how AI in accounts payable may change in the not-so-distant future.
Conversational AI
You’ve likely already had an interaction with a conversational AI in the form of a chatbot. So, how could that technology be integrated into and impact the AP process?
The same tech that powers chatbots could be used to power your own personal support bot. This could be customer-facing, providing support to your vendors, or user-facing, with tips and advice based on the data it has on hand.
Imagine opening up the platform and merely asking the questions you want answers to, rather than searching for them yourself. This is within the realm of possibility with AI in accounts payable.
Truly touchless accounts payable
As the cognitive abilities of AI expand, so too does the complexity of the tasks it can complete. This could mean processing invoices, scheduling payments for a time that’s optimal for a business’s cash flow, and handling vendor communications, minimizing human input to a simple approval.
More integrations with existing tools
Most AI-powered AI solutions are limited to learning from the business’s data that it has access to. The possibilities start expanding once it has access to even more information.
If the AP platform can be integrated with a bank account, the AI could be trained on cash inflows and outflows, finding perfect windows of opportunity to send payments.
Perhaps it’s provided access to external datasets like industry benchmarks to provide insights on how the business is performing against the standard. Or it will incorporate industry trends into its forecasting practice.
Working with the blockchain
Incorporating blockchain technology would enhance the security and transparency of the accounts payable process. With a secure ledger of all transactions recorded, there’s a clear history of payments for the AI to learn from and work within.
An AI-powered AP platform that works for you
Implementing AI in your accounts payable process doesn’t need to be complicated. BILL has saved its clients precious time on their accounts payable for years, making the right choice for ai accounts payable software.
Try a risk-free trial to see our automation in action and see just how much time it’ll save you in your workflows.
Frequently asked questions
What tasks can AI in accounts payable do?
AI automates information capturing, data entry, validation, and processing to streamline the entire workflow. When human input is required, automated notifications are sent out, prompting action and ensuring there isn’t a bottleneck.
Can AI work with different invoice formats?
Yes, AI adapts easily to PDFs and digital formats. Even if a vendor is using paper invoices, simply snap a clear photo or scan the document and the AI will use OCR to take the essential information from the document.
Will AI replace accounts payable teams?
No, AI is not designed to replace AP teams. AI-backed AP platforms are designed to simplify the work for AP terms, not replace them entirely. Instead, AP teams will have more opportunities to focus on high-value, strategic initiatives.
What’s the ROI of implementing AI in accounts payable?
The ROI of implementing AI depends on how many invoices the business processes and how much time it saves. Read our guide on calculating the ROI of accounts payable automation for more information.
