Automation solutions are not interchangeable: find the best option for PO Matching

Purchase Order (PO) matching is a tedious process when done manually. Fortunately, as technology continues to advance, organizations have more access to automated solutions. One common option is a combination of Optical Character Recognition (OCR) and Robotic Process Automation (RPA). However, the emergence of Artificial Intelligence (AI) has brought new possibilities to the table. Learn how these technologies work and why AI provides true automation.

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OCR and RPA Technology for PO Matching:

Automation for PO matching has traditionally been served by a combination of OCR and RPA technologies. OCR, which converts scanned or printed text into machine-readable text, can extract data from POs. Coupled with RPA, which automates repetitive tasks, OCR can streamline the PO matching process. Specifically, these technologies can be leveraged to do:

1. Data Extraction: OCR extracts data from POs by converting physical documents into digital formats. This reduces manual effort and improves accuracy.
2. Process Automation: From there, RPA takes the OCR-extracted data and automates routine tasks associated with PO matching. This rules-based system can automate data entry, compare information across systems, and generate reports. The result is a streamlined process that saves time and reduces errors.
3. Integration: OCR and RPA technology can plug into existing legacy applications and databases.
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Limitations of OCR and RPA for PO Matching:

While the combination of OCR and RPA can automate components of PO Matching, it can only take AP departments so far since it consistently requires work to program and maintain. These challenges include:

1. Limited Data Extraction: OCR technology is heavily dependent on templates, which means it may struggle when extracting data from complex PO formats or handwritten documents. This makes it prone to errors when faced with format anomalies.
2. Lack of Contextual Understanding: Since OCR and RPA are rule-based systems, they cannot understand the context behind the extracted data. This limits their ability to interpret unstructured data or make intelligent decisions when faced with discrepancies, exceptions, or changes in PO formats.
3. Inability to Adapt: Any time a change or update is made to PO formats or document types, OCR and RPA systems need to be manually programmed.
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Why AI is the right choice for PO Matching:

Enter Artificial Intelligence (AI). AI introduces advanced capabilities that surpass the limitations of OCR and RPA, making it the right choice for automating PO matching. Here's why:

1. Enhanced Data Extraction: AI-powered solutions can accurately extract data from all types of documents, including complex POs and handwritten documents. With machine learning models, AI can understand and interpret unstructured information, increasing the accuracy of PO matching while reducing effort.
2. Contextual Understanding: AI models can comprehend the context behind the extracted data, which allows them to intelligently make decisions during PO matching. They can automatically identify discrepancies, handle exceptions, and adapt to changes in PO formats.
3. Adaptability and Scalability: AI models get better over time as they ingest more data. This lets them adapt to evolving business requirements without extensive manual configuration and programming.
4. Error Reduction and Efficiency: By automating the process end-to-end, AI-powered PO matching significantly reduces errors and enhances efficiency. By eliminating the need for human intervention in routine tasks, AP teams can focus on higher-value activities.
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Get true PO Matching autonomy with AI

While OCR and RPA have made strides in automating PO matching processes, breakthroughs in AI will accelerate innovation in this space over the next few years. AI's ability to interpret complex data structures, adapt to evolving scenarios, and make advanced decisions surpasses the limitations of OCR and RPA. By leveraging AI technology, organizations can achieve higher accuracy, efficiency, and automation in their PO matching processes, ultimately leading to streamlined procurement operations, and enabling finance departments to intelligently scale their teams.

What to learn more about the future of PO Matching? Learn how Vic.ai’s Autonomous PO Matching takes companies even closer towards truly autonomous accounting.

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