PO Matching involves linking a purchase order issued by a client to the corresponding invoice from a vendor, ensuring accurate payments and fraud prevention. Manual PO matching is a labor-intensive and error-prone process, particularly in large organizations, due to the handling of diverse document formats and extensive human involvement. Automation, through technologies like Optical Character Recognition (OCR), Robotic Process Automation (RPA), Artificial Intelligence (AI), and Machine Learning (ML), enhances efficiency by digitizing and streamlining the process, reducing errors, and providing features like smart matching, touchless processing, and audit readiness. AI-based systems can extract, recognize, and match data, flag errors, and allow the accounts payable team to focus on strategic tasks rather than manual data entry. Implementing AI-enabled PO matching involves integrating with existing systems, planning for contingencies, and ensuring comprehensive data handling. Popular tools like Nanonets, Oracle, and Sage Intacct offer AI-enabled PO matching solutions, aiming to reduce processing time and costs while enhancing productivity and compliance. AI is poised to transform accounting practices, though it will complement rather than replace human accountants, emphasizing a harmonious integration of technology and human oversight to maximize efficiency and strategic value.