So, what should finance leaders do to address these issues and position their firms for the future?

This leads to the concept of Autonomous Finance. This concept is gaining momentum, with software authors like Microsoft investing heavily in incorporating these capabilities into their products. Autonomous Finance is the application of AI, machine learning, and advanced analytics to manage financial tasks and decisions with minimal or no human intervention.

Essentially, accounting processes run mostly unattended in the background, highlighting issues and notifying you of exceptions you need to focus on. The goal is to automate repeatable financial processes to improve productivity levels and reduce errors, which can then help finance departments pivot to more strategic activities to provide the business with better real-time insights, giving them more of a stake in the financial strategy of the organization.

The quote from Gartner speaks to why accounting is a natural business function for autonomous processing: namely, it is all based on numbers and rules. And workflows are generally straightforward, so firms can reap substantial financial benefits from autonomous finance initiatives.

This is important to most organizations because it can have a significant impact on lowering administrative costs and providing other benefits to the organization. Firms that have implemented autonomous finance solutions report productivity improvements of 20-40% overall, including 90% in the AP process alone. With autonomous finance in mind, finance leaders can do two things right now to position for the future:

• Integrate your financial processes on a modern cloud financial platform. Migrating away from older technology and disparate point systems and moving to an integrated financial management platform that’s built on modern cloud technology and has the ability to easily leverage emerging technologies, such as AI, can help you drive better automation levels and insights.
• Focus on automating non-value-added processes within your accounting team. Look for opportunities to automate repeatable processes, move away from manual data entry and processes, and begin managing by exception to free up time to focus on more strategic initiatives, such as being more proactive in helping to support business planning and forecasting activities and working on advanced analytics and insights to see what’s happening within the business to support leadership in making strategic decisions.

For most firms, AP is a highly manual process. The accounting team receives invoices from subs and other vendors, types them in an AP invoice record—often scanning and attaching a copy of the invoice—and sending it out for approval, likely from the PM if it’s project-related. This approach takes too long by today’s standards. In fact, Aberdeen Group measured the time and cost to manually process AP invoices and found that the average cost is $16.91 in internal labor costs because so many people touch the process. It’s also very time-consuming to investigate exceptions and correct errors. All of this can cause delays in closing out AP at month's end.

This is a perfect process for autonomous finance, applying AI to run largely automated and unattended in the background, leaving only exceptions for humans to work on. This new process also provides AI-driven insights to deal with the errors and exceptions that need to be addressed.

The built-in AI engine in Microsoft Dynamics 365 Finance can ingest invoice documents, extract key details (dates, vendors, amounts), create and code the AP invoice, and if it meets the confidence rules, send it out for approval by the PM or whoever is set up as the approver, and then automatically create and process the AP payment record for you. If you prefer to have some human touch in the process and want to review it and post the payment, that option is available, but the AP payment could be automatically posted and sent out electronically through Dynamics 365’s autonomous banking.

In situations with exceptions, Dynamics 365 provides a convenient dashboard showing progress. Embedded Copilot AI can help do things like find and suggest data to update or suggest potential matching transactions to help speed things up even more.

For most organizations, forecasting cash is done with limited information. You can use customer invoice dates, payment terms, and due dates to forecast cash receipts, but you can’t determine when the customer might actually pay the invoice based on past behavior. AI and machine learning can help with this.

Instead of looking at partial, static data like when an invoice is due, AI and machine learning technology can look at customer payment history for similar types of invoices, similar amounts, and at a similar time of year, and then make a prediction of when the customer is likely to pay based on that information. It learns and gets smarter as it gathers more data. The result is more accurate payment expectations, more accurate cash flow forecasting, and better risk management by getting out in front of potential collections issues.

This rolls into more intelligent cash flow forecasting based on when cash is more likely to be coming in the door.

Another area ripe for autonomous finance is banking. Typically very manual in nature, banking involves uploading and downloading files such as bank statements, AP payment files, and positive pay files, manually reconciling bank statements, manually processing cash receipts, and settling client invoices. These are all tasks that are ideal for running autonomously — uploading and downloading bank files unattended and automatically reconciling bank accounts and settling invoices.

Dynamics 365 can directly connect to your banks to automatically download bank statements and reconcile bank accounts for you, providing a workbench for managing exceptions. This same concept applies to any sort of file or feed you can get from your bank for cash you’ve received from clients, whether it be a lockbox account or something similar. Dynamics 365 can automatically download that file and then auto-match and settle any invoices that are within the tolerance and rules you set up.

Again, you are only working on exceptions. This is another area where Microsoft is working on Copilot capabilities to suggest data changes or find potential matches to help you quickly manage these exceptions and then automatically transmit AP payment files like EFT or ACH payments when you post an AP payment batch, as well as automatically sending out a Positive Pay file if applicable.

Like banking and AR, this process is highly suitable for automation and running unattended where appropriate. Most firms manage the period close process using an offline task list that is typically tracked in Excel, and the accounting team must manually touch every step in the close process. Because it is tracked offline in Excel, it is difficult to track where you are in the process and analyze which of these steps are taking too long, slowing down the process and delaying financial reports.

In an autonomous finance world, an online period close checklist contains all the tasks that need to be completed. AI can automatically complete them where appropriate; however, you have visibility at all times into where things stand. This significantly reduces the time it takes to close the books. Dynamics 365 and aec360 have the ability to do just that.

So, in AR, for example: run the currency revaluation, generate AR statements, calculate interest, send collections letters, reconcile to the GL, stop the period, and so on. Dynamics 365 can also use generative AI to provide narratives of how processes are going and provide analytics around where they stand, where steps tend to get interrupted or slow down, and how long they are taking.