Invoice Automation: From 45 Minutes per Invoice to One Click

One wrong number on a supplier invoice can stop it from being paid. If the price, quantity, or purchase order (PO) number doesn't match the PO on file, someone has to find out why, contact the supplier or procurement, and fix the record before the invoice can move. These mismatches, or exceptions, are the top challenge for accounts payable (AP) teams.

Invoice automation is supposed to cut the time a team spends handling exceptions, but a tool can only save time on the steps it automates. Before you choose one, know which actions take the most time when processing an invoice.

Fluency measures how long each action takes by observing work as it happens. In one company's supplier invoice operation, it recorded how long the process took, including every exception. The company then automated invoice processing, with an AI agent doing most of the work. After automation, its AP team went from spending 45 minutes on an invoice to about one minute.

Once you know where your team's time goes, you can automate the longest steps first and skip tools that only save a few minutes per invoice. By the end of this article, you'll know how to break invoice processing into actions, which of those actions a tool can take over, and what to measure before you use AI to automate the process.

TL;DR

• The automation covers the whole sequence. In this operation, an AI agent runs four of the five actions and prepares the fifth for a person to confirm with one click.

• Human time per invoice fell from 45 minutes to about one minute, measured against a baseline recorded before the agent went live.

• Extracting data and matching POs took 9.8 of the 45 minutes. A tool limited to that action can remove, at most, 9.8.

• Invoice processing runs through six steps from receipt to payment. Software can run steps two through four when an invoice matches cleanly, and people handle the exceptions.

How invoice processing works in a large company

The accounts payable process covers everything between a supplier sending an invoice and the company paying it. It generally runs in six steps:

1. The supplier sends the invoice by email, a supplier portal, or paper, and the company logs it.
2. A person or software that reads invoices enters its details, such as the supplier, amounts, line items, and PO number.
3. The invoice is compared with the PO and with the receiving record, which confirms the goods or services arrived. When all three agree, the invoice can move on to the next step.
4. Each line is coded to a general ledger account (the type of expense) and a cost center (the department that spent the money).
5. An approver confirms the invoice for payment.
6. Finance records the invoice, schedules the payment, and closes it out.

Software can handle steps two through four when the invoice, the PO, and the receiving record agree, then send the invoice to an approver for step five. When they don't agree, the invoice becomes an exception, and a person takes over. Common mismatches include a price that differs from the PO, a missing PO number, a quantity that doesn't match what arrived, and a duplicate invoice. The person contacts the supplier or procurement, fixes the record, and sends the invoice back through matching and approval.

Ardent Partners' 2025 AP benchmark puts the average cost to process one invoice at $9.40 and the average processing time at 9.2 days, which includes every hour an invoice sits waiting for someone. Exceptions stretch that time, because each one adds a round of follow-up before the invoice can be paid.

The 45 minutes from the operation Fluency observed count only the time a person spends working on an invoice, such as reading it, entering data, and emailing the supplier. Waiting time and time spent on other work aren't included.

Where the hours go in invoice processing

In the operation Fluency observed, a person spent 45 minutes on each invoice, and most of that time came after the invoice was read and checked against the PO. The process split across five actions:

Fluency observed 88.3 total hours of this operation's invoice processing, covering every path an invoice took, including the exceptions. Each action's share of the 45 minutes matches its share of those observed hours. For example, updating records took about 40% of the observed hours, so it accounts for about 40% of the 45 minutes, or 18.

Teams that estimate their own time tend to leave steps out. People remember the main task and forget the steps around it, like updating records and following up on messages. In this operation, those two actions took 27.8 of the 45 minutes.

What to automate in invoice processing, and what to keep with people

An AI agent can handle four of the five actions:

• Reading the invoice and checking it against the PO
• Updating the company's records and preparing the financials
• Writing and following up on messages about the invoice
• Finalizing the records and closing out the invoice

For the fifth action, the agent prepares the transaction, and a person reviews and approves it with one click. Approval stays with a person for accountability, since this step controls who the company pays.

The before-and-after is starker than five actions suggest. Across every path an invoice took in this operation, there were 197 separate steps and 54 points where a person had to step in. The agent now runs the same work as five actions with one approval.

An automation follows the steps it was built on. If someone handles an invoice a different way, or procurement changes the PO format, the invoice goes back to a person until someone rebuilds the automation. Every time that happens, the team is back to processing invoices by hand, so the automation saves less than the team planned for.

Fluency keeps observing the work and updates the agent as the process evolves, so the team doesn't have to rebuild it. What it observes builds a work ontology, a continuously updated map of who does the work, what they do, which documents they use, and where they hand off to each other. The ontology recognizes the different ways people handle an invoice as the same task, so one agent covers all of them, including the exceptions. Your team keeps the time it planned to save, even as invoices vary and the process changes.

Fluency's guide to ranking the work worth automating shows how to decide which steps get automated with software or an AI agent, and which stay with a person.

What changed after automating invoices

Since the agent went live, a person spends about one minute on each invoice instead of 45. Approval, the only step not automated, used to take 3.3 minutes. Now the agent has the transaction ready before the approver opens it.

That gives the team back about 44 minutes per invoice. As invoice volume grows, the same team can keep up without falling behind.

Fluency measured the before and after the same way, by observing the team's invoice processing before deploying the automation and after. Because both numbers come from the same measurement, the team can show finance the return on the deployment.

Your team will need the same before-and-after measurement to measure ROI across systems. System records can't give it to you. A cross-functional process like procure-to-pay runs through several systems and apps, and each one logs only its own steps, while part of the process happens between them. Fluency's Automations feature measures every agent it deploys this way, so you can see what each one returned before you choose what to automate next.

Invoice automation solutions

Each of the tools below automates invoice processing to a different degree, and each handles exceptions in its own way. The best one for you depends on which parts of the process take the longest and how many of your invoices end up as exceptions.

Fluency: finding the work and deploying the agent

Fluency is a work intelligence platform that shows large enterprises where AI will have the biggest impact by finding the best work to automate first. It observes work at the point of execution, deploys AI agents to automate work, and measures results against an observed baseline.

For invoices, Fluency shows where the hours go before a company commits to a tool, including the work between systems, which system logs don't record. Its Opportunities feature ranks automation candidates by ROI, so your team can see which part of the invoicing process to automate first.

In the operation above, Fluency's agent took over four of the five actions and prepared the fifth for a person to approve, across every path an invoice took, including the exceptions. Fluency builds and maintains the agent from the work it observed, using the work ontology.

Fluency installs in under an hour with no direct access to company systems. It captures no keystrokes or screen recordings, and nothing it collects ties back to an individual.

---

Stampli: AP automation platform

Stampli's AP automation software is built for AP teams that want one platform for reading invoices, coding them, matching them to POs, and routing approvals. It reads invoice data with OCR and AI, fills in coding from the company's own accounting codes, and checks for duplicates. Approvers, colleagues, and suppliers can answer questions about an invoice inside the invoice itself.

---

Rossum: document capture

Rossum's accounts payable automation reads invoices in many layouts and languages without templates. It codes invoices to the general ledger and tax accounts, matches them to POs and receiving records, and posts them to the ERP or accounting system. When an invoice doesn't match, Rossum's page says AP staff resolve it in Rossum's interface.

---

UiPath: robotic process automation

UiPath's invoice automation solution runs on UiPath's automation platform, which combines AI agents, software robots, and people. It covers invoice intake, checking, matching, approvals, and posting to the accounting system, and it routes exceptions to a person for review.

See where your invoice hours go

You can't know how much invoice processing time a tool will save until you know where your team's time goes. Request a Fluency demo to see how Fluency measures the time each invoice takes, which actions take longest, and what a deployed automation looks like.

Invoice automation FAQs

What is invoice automation?

Automated invoice processing means software performs steps of the invoice process that were once done by hand, including reading invoice data, matching it to POs, coding it to accounts, routing it for approval, and posting it to the accounting system. Tools differ in how many of those steps they cover and in what happens when an invoice doesn't match.

What is the best way to automate invoice processing in a large company?

Start by observing how long people spend on each invoice today, including the ones that don't match their POs. Teams tend to underestimate their own time. Then automate every action people spend time on, including the ones after reading and matching. Have a person approve the invoice, because someone has to stay accountable for what the company pays. Measure the process before and after the automation so you can see its return. In the supplier invoice operation Fluency observed, human time per invoice fell from 45 minutes to about one minute.

How long does invoice processing take?

Ardent Partners' 2025 benchmark puts the average at 9.2 days to process a single invoice. Days measure elapsed time, including every hour an invoice waits for someone. Hands-on time is a separate measure. In the supplier invoice operation Fluency observed, a person spent 45 minutes on each invoice before automation and about one minute after.