AI (Artificial Intelligence) is a pivotal topic in today’s digital age, with advances in Large Language Models (LLMs) making advancements in nearly every professional domain. Within the vast sphere of AI potential, accounting has emerged as a clear contender for digital transformation due to the traditional operations’ manual nature and repetitive tasks, such as data entry, paperwork, and extensive processes in handling payable functions.
Yet, introducing AI to accounting doesn’t mean undertaking a complete overhaul, despite widespread belief. Rather, even basic AI automation can significantly transform the accounting function, once suitably implemented and integrated. For instance, optical character recognition (OCR), present for decades and representing simple automation, can decrease invoice processing time by at least 60%. However, technology adoption such as OCR remains slow as apprehension toward AI reliance persists.
Despite apprehension, AI and machine learning can drastically reduce human error potential, improve processing optimizations, and provide greater data accuracy and robustness the more frequently the system is used. For instance, crucial tasks in the accounting process, such as invoice coding, General Ledger (GL) mapping, fraud and duplicate detection, and other similar manual repetitive processes, are ideal for AI integration.
AI and machine learning, if appropriately implemented, can analyze data at a far greater capacity than humans and identify inaccuracies or patterns more quickly. Examples include automating invoice coding based on LLM processing, remembering user inputs once a GL code is selected, detecting duplicate entries and incorrect information, conducting multiple validations on invoice data, and learning simple repeatable actions.
As with any AI integration, appropriate and continued system training is crucial for sustained system accuracy and functionality. Trained AI systems can also learn the user’s recurring behaviors and use them in their processing, meaning that AI assistance in accounting will not only help now but improve as it continues to be used.
Companies such as Nanonets offer AI platforms that can be smoothly implemented into existing accounting processes. For those open to embracing the digital transformation, these platforms can substantially enhance accounting operations, reducing both processing times and human error rates, while continuously learning and improving from their interactions. The future of accounting lies in AI and digital transformation – with the only limit being how far companies are willing to explore automation and machine learning.
