Artificial Intelligence in Accounting
As artificial intelligence (AI) evolved, it started to be applied in a wide range of industries and functions. Its use allowed for the automation of data processing and handling. Many AI functions involved the use of robotic process automation (RPA) as a tool and machine learning skills to imitate human thinking. It could lead to increased productivity, improved accuracy in data input and processing, optimized revenue, and reduced cost. When AI was used in the accounting function, it could be applied in the areas of accounts payable, accounts receivable, procurement, expense management, consolidation, and trading management, among others. The results also assisted with internal control, compliance, and auditing as well as in making more informed management decisions. Radial Tires Company (RTC) manufactured radial tires in mainland China. The company was headquartered in Hong Kong, with five manufacturing plants in Shangdong and Jiansu. In a recent meeting with the holding company, David Lee, RTC's CFO, was told that from the next financial quarter on, the holding company required that RTC provide more extensive reporting and shorten reporting time. Lee was considering the use of AI technology to achieve this. But he had no experience with using AI for accounting and neither did his contacts at other manufacturing enterprises. Lee contacted FlexSystem, RTC's existing accounting and enterprise resource planning (ERP) software provider. FlexSystem would advise on the use of RPA, other AI tools, and automation processes to work with RTC's ERP and accounting software. It would also develop a proposal for RTC in which it would present a workflow using various IT solutions and describe how they could improve speed and efficiency in accounting processes, the estimated project time required and recommend key performance indicators to measure results and return on investment (ROI). Once FlexSystem completed the proposal, Lee, other department heads, and his CEO had to decide which IT solutions to apply. Key decision criteria included the costs and learning process involved on the one hand and the benefits of the automation processes on the other.