Modernizing Invoice Processing with U-M GPT

Shared Services - Accounts Payable

Problem

The Shared Services Center processes approximately 300,000 invoices annually, extracting key information from vendor-submitted vouchers. Previously, this process relied on a template-based system implemented in 2019, which was revolutionary at the time but had limitations, processing only about 30% of invoices. With the sunsetting of this older technology, a new AI-driven solution was needed to enhance efficiency, accuracy, and scalability in invoice processing.

Audience

The Accounts Payable team at the Shared Services Center.

Outcome/Impact

The transition to a UMGPT-powered invoice processing system has significantly improved workflow efficiency and accuracy across multiple teams:

  • Higher Automation Rate – The new AI-driven tool can process a much larger percentage of invoices compared to the previous system, reducing manual workload.
  • Faster Processing Times – The imaging team, responsible for initial triage, now handles a lower volume of tickets, as the majority of invoices are processed automatically.
  • Streamlined Payments – The outgoing payments team receives and reviews invoices more quickly, eliminating delays caused by manual processing.

By leveraging U-M GPT, the Accounts Payable team has modernized its operations, ensuring faster and more efficient invoice-to-voucher processing while freeing up staff to focus on higher-value tasks.

*** Doug Rose, Matt Dupie, and the Accounts Payable team at the SSC created this AI project.