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Faced with shifts in client expectations, strained bandwidth, and a revolving door of regulatory changes, more and more accounting firms are turning to technology to automate workflows and improve operational efficiencies. For firms that have not yet done so, now is the time to take a closer look at robotic process automation (RPA).
With support from advanced technologies like artificial intelligence (AI), and a rise in low-code and no-code development, the software bots are poised to increasingly strengthen their foothold within the accounting profession.
To help tax and accounting firms better understand RPA, this article takes a closer look at how RPA is defined, how it differs from AI, and how RPA can be used in accounting.
Robotic process automation is software technology that fully or partially automates repetitive, manual, rules-based tasks. In other words, it replicates the actions of a human when they use software to handle mundane tasks like data entry, web scraping, and processing standard transactions. This is why some professionals also refer to software bots as “virtual assistants.”
“It is really a step-by-step process that the human would take, like a workflow process that is step-by-step, and the robot does the same things for you. It just repeats the steps as often as you want to schedule it or run it on demand,” said Dustin Teribery, API Sales Specialist for Thomson Reuters. “It just does exactly what you tell it to and exactly what you are doing.”
Teribery noted that RPAs can prove especially beneficial for firms using legacy or homegrown software that doesn’t have a back-end application programming interface (API) or other automation capabilities.
As outlined by the Association for Intelligent Information Management (AIIM), RPAs serve several purposes:
Both RPA and AI are automation technologies that can help firms improve efficiencies; however, it is important not to confuse the two as there are stark differences.
RPAs are process-driven bots that follow only the instructions they are programmed to perform. RPAs are not able to learn new procedures or methods, which means they must be maintained and updated.
AI, on the other hand, is data-driven intelligent automation. AI is designed to simulate human intelligence. It can recognize patterns in data, including unstructured data, and has the ability to learn and “think” through processes. This means that AI is used for more than strict rules-based processes and applied to more complex scenarios.
Despite the differences, one should keep in mind that leveraging both RPA and AI is beneficial as the automation technologies can complement each other quite well.
For instance, as noted by IBM, “AI can help RPA automate tasks more fully and handle more complex use cases. RPA also enables AI insights to be actioned on more quickly instead of waiting on manual implementations.”
To summarize, here are some key points to keep in mind:
It is no secret that accounting firms are increasingly looking for ways to improve efficiencies and drive greater profitability. RPAs are a great way to automate repetitive, mundane tasks in bookkeeping, invoicing, tax compliance, accounts payable or receivable, payroll, expense management, and more. This eases the strain on staff and provides them with more time to focus on higher value, higher margin work.
The applications of robotic process automation within accounting varies depending on the firm’s needs, but a good place to start is to think of those repeatable, mundane tasks that are a drain on time and efficiency. Which tasks do you always put off to the last minute? Which tasks would you pass on to an assistant if possible?
To illustrate possible use cases, Teribery pointed to Thomson Reuters Practice CS on-premise software because it does not enable the use of APIs. This makes RPA an ideal fit for Practice CS.
“Since Practice CS does not have APIs, using RPA would make it possible to log in and print reports from inside the software. The best thing is that to Practice CS, the RPA process is just another human logging in. No modifications are needed,” Teribery said.
In addition, consider those tasks that AI cannot complete. For example, if your firm leverages Microsoft Copilot, an RPA can be programmed to automatically retrieve, download, and email you meeting notes.
“It is really using RPA for the steps that something else can’t complete. AI won’t email [the meeting notes] to you. After every meeting, you have to go into Copilot, click the download button, and go save it somewhere. Why not have RPA click the download button, hit the save button, save it to a location, and attach it to an email?” said Teribery.
The notion of implementing RPAs seems daunting, but it doesn’t have to be. This is due, in part, to the rise of no-code or low-code RPAs. As the name suggests, no-code eliminates the need for any coding. Meanwhile, low-code uses pre-built components and visual interfaces to help simplify implementation.
In general, there are several factors that firms should consider when looking to implement RPAs:
It is also important to keep in mind that combining the strengths of RPA with AI is game-changing. Through this winning combination, tax and accounting firms can improve operational efficiencies and achieve the competitive edge needed in today’s complex environment. To learn more about how firms are using new technologies, read the 2024 Generative AI in Tax Firms report.
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