In this summary, we cover:

  • How the RPA/AI, has transformed the audit process
  • The stages involved in running RPA
  • How RPA can be used in accounting firms


  • RPA has greatly transformed audit processes by assisting with tasks, giving good data accuracy and handling repeatable processes.
  • Understand the difference between RPA and AI because RPA is not exactly AI. RPA needs to be fed with specific rules-based processes whereas, AI doesn’t because it can make connections and reach meanings without relying on pre-defined rules.
  • It is important to note that running RPA requires three stages. Which are; process understanding, Audit data standardization, and Execution of RPA based audit test.
  • You can use RPA in making analysis and reconciliation. It can also be used in Dual-purpose audit tests which involve, calculating differences in prices and quantities.
  • It is essential to know that since RPA are not fully artificially intelligent yet, both RPA and AI can both be implemented to serve the same purpose.


The RPA has become an important automation tool that drives transformation and aids future work. It is also a user-friendly and an effective tool which has mostly garnered attention in the business world, especially in public accounting firms as it has increasingly worked as an assistant, assisting employees in tedious tasks, enabling them to concentrate on other revenue generating tasks for an organization.

RPA and AI

The RPA and Artificial intelligence

Artificial intelligence (AI) is a type of machine or system that can learn on its own. They can make connections and reach meanings without relying on pre-defined rules. Artificial intelligence is different from RPA in the sense that, the robotic process automation (RPA) are software robots, they are therefore not fully artificially intelligent because these software robots must always be provided with specific rules -based processes and they cannot fully handle ambiguity on their own as it needs to be broken down properly for the software.

However, there are some few case studies where firms have implemented RPA not AI. Why is this so? RPA is good at data accuracy, compliance, and repeatable processes whereas AI doesn’t need to be fed with structured data. But the RPA and AI can both be implemented to serve the same purpose since they both complement each other.

How did RPA transform the accounting/auditing process?

Originally, auditing used to be done with computer dependent tools, which were linked by manual processes and keystrokes. However, with the emergence of new software tools, it has combined all these long processes into a single, smooth running automated process.  It is this software tool that RPA uses to transform a manual audit into an accurate audit process. The impressive thing about RPA is that it makes the whole audit process better as it can be said to have transformed the audit and accounting process in many ways like; presenting a disruptive change in the audit process, carrying out a repetitive task more quickly, accurately and tirelessly, relieving the accountants in performing some tasks like copying and pasting information, and finally, improving the audit quality which improves business services.

RPA can also be used in:

      • Reconciliation and analytical procedures; RPA, can be used in reconciling and making an analysis. For example, it helps the auditors to calculate a client’s total revenue amount by retrieving the client’s audit evidence, calculating the total sales per listing and then comparing it to the total of each trial balance. If the total revenue from the current or previous year listings is different, the RPA generates an alert.
      • Dual-purpose audit tests; the RPA can also be automatically programmed to calculate differences in prices and quantities on sales invoices, shipping documents etc. once these differences in prices and quantities are spotted, it generates alerts for those different transactions.

In order for RPA to be run /put into practice, according to the RPA implementation roadmap, it has to undergo three stages. They are;

      • Process understanding; now each and every audit process needs to be understood and well broken down into small audit modules to ensure proper interpretation by the software programs. This is done because mostly, the task of importing data or exporting data is easily understood by a human user and not for a software program as it still needs to be broken down into bits and pieces.
      • Audit data standardization (ADS); this stage majorly, is for accounting firms to create an audit data standard for every process that will be replaced by the RPA. Most accounting firms now make use of ADS as its becoming more relevant in the use of financial statement audits.
      • Execution of RPA based audit test; this is the final step when it comes to putting RPA into practice. Here, the software is automatically programmed to execute audit tests. Audit tests should be programmed as rules-based functions that would enable automatic execution of audit tests.

Finally, RPA and AI should both be implemented in accounting firm so that where the RPA cannot meet certain audit objectives, artificial intelligence would. But according to research, most people fear that artificial intelligence might fully take over human tasks thereby rendering workers irrelevant for some tasks. In as much as this is an understatement because artificial intelligence is not made to take over human tasks but to make human tasks more easy and accurate, it is, however, important to note that most public accounting firms prefer RPA to AI.