Accounts Payable Invoice Automation: One of the Best Applications of AI

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We believe that the figure depicted in the Gartner Infographic indicates that accounts payable invoice automation is one of the best applications of artificial intelligence in a business, both in terms of business value and in terms of feasibility. According to Gartner, “AI-based accounts payable invoice automation tools use machine learning to match invoices to purchase orders (PO), contracts, or automatically code without a PO. This minimizes human input in processing invoices reduces late payments, and creates opportunities for early payment discounts.” Additionally, the Gartner study shows that the use of artificial intelligence in AP automation reduces costs, increases efficiencies, improves user experience, reduces risk exposure, and is very doable.

While the technology is still new, there are already improvements to be made within accounts payable by increasing the level of automation to a place where AI can play a more significant role. Most commonly, accounts payable has seen the application of AI in automated workflows and matching that use software to determine how to route and match invoices based on data in the invoice. While this still requires coming up with a set of rules for the software to follow, machine learning has been successful in using historic data for scenarios of present transactions where it can recognize and mimic patterns.

The application of artificial intelligence to accounts payable invoice automation allows departments to further increase the efficiencies and speed of their invoicing process. As more companies choose to automate and utilize AI in accounts payable automation, technologies will continue to advance to better serve the needs of complex departments. Artificial intelligence is becoming a more important tool to have in business, so it’s important to put it in place where it makes the most sense first, and that’s as part of accounts payable invoice automation.

Gartner, “Infographic: AI Use-Case Prism for Sourcing and Procurement”, Saniye Alaybeyi, Geraint John, Patrick Connaughton, Farhan Choudhary, Published: 30 March 2021

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