Processing invoices is a critical task for accounts payable departments, as accurate and timely processing ensures financial clarity and avoids potential disputes. Invoice data extraction, which involves pulling data from invoices to analyze and process them further, has improved with advancements in artificial intelligence (AI) invoice processing. This article explores different invoice extraction methods, including manual data entry, template-based OCR extraction, and automated invoice data extraction using OCR and AI. It also discusses the challenges of extracting data from invoices, such as format diversity, data complexity, accuracy issues, and business complexities. The article highlights the benefits of automated tools, which can handle large volumes of diverse formats without pre-defined templates, extract key data fields with high accuracy, and recognize text from scanned documents. To prepare invoices for extraction, it is essential to adopt a consistent file naming system, convert paper invoices to digital format, clean and preprocess the invoice data, normalize the data, and perform text cleaning and data validation. The article concludes that automated tools can significantly improve efficiency and accuracy in invoice processing, making it an attractive solution for businesses with high invoice volumes or complex, varied invoice formats.