Data entry, a crucial task for various industries, involves the manual conversion of physical documents into digital formats to derive insights, but it is traditionally plagued by inefficiencies such as high error rates, costs, and security risks. The advent of AI and machine learning offers a solution through automated data entry, which significantly improves accuracy, efficiency, and scalability. Technologies like Optical Character Recognition (OCR), Natural Language Processing (NLP), and deep learning play pivotal roles in enhancing data entry processes. AI-based automation reduces errors, operational costs, and manual labor, increases data security, and supports real-time analytics, scalability, and improved financial management. Implementing AI tools involves assessing organizational needs, selecting appropriate technologies, and ensuring effective integration and training. As AI tools continue to evolve, they are expected to further transform data entry, particularly with advancements in related fields such as robotic process automation and intelligent document processing.