How to measure the return on investment of AI in accounting


AI has the qualities that make it an ideal solution for automating financial accounting.

It is important to quantify the results obtained by these qualities to obtain an accurate estimate of the return on investment of AI in accounting.

Accounting is a function that demands extreme diligence, precision, and analytical ability, all of which AI has in spades. While AI’s massive data-processing capability has always been a boon for accounting teams in organizations, its newer subsets such as natural language generation and computer vision have completely reshaped the field of accounting. and financial information. However, accurately assessing the ROI of AI in accounting is a task that can challenge even the most advanced AI accounting tools. This is because it involves a combination of many real and hypothetical elements, as follows:

Number of working hours saved

The most obvious benefit of using AI in accounting is the number of working hours it allows the accounting team. Accounting involves many activities that require tedious data entry and analysis. Using tools like computer vision and optical character recognition (OCR), AI-based accounting tools ensure that data from different sources is instantly brought together and categorized where it is needed. The number of working hours that would otherwise be used to classify and reconcile accounting records by an organization’s accounting team can be recorded as a component of ROI. It is the simplest component of the ROI calculation for AI in accounting.

Cost of non-compliance

The main reason organizations have specialized accounting teams is to comply with financial regulations. A team of trained accountants, supported by modern AI tools, help companies avoid heavy financial penalties, damage to their reputation and loss of goodwill. The calculation of the return on investment of AI in accounting should therefore include the cost that the company would have paid in the event of non-compliance. However, it can get a bit complicated as the penalties for different types of non-compliance may differ and not follow a standard pattern. In addition, the cost of non-compliance cannot be accurately assessed until it is actually imposed, and therefore the money saved through compliance is a purely hypothetical estimate.

Earnings thanks to precise predictions

Businesses use historical financial data to make forecasts and plans. To do this, finance and accounting teams perform analysis on financial data using AI algorithms to optimize financial planning. However, just like the savings from compliance, the financial gains from accurate AI predictions are difficult to quantify. Therefore, the cost of accurate predictions cannot be established with absolute certainty.

These components of the return on investment of AI in accounting can be calculated by applying various approximation and extrapolation techniques. In order to get a reasonably close estimate of ROI, companies should consider both historical company data and industry benchmarks.


Comments are closed.