AP automation moves fast, and the terminology can be confusing if you don't work in tech. Here's a plain-language guide to the terms and approaches you'll come across when evaluating automated invoice processing.

Software providers and accounting firms can sound alike when they talk about AP automation, but the technology underneath can be very different. Knowing the terms helps you ask the right questions and compare what you're actually being offered.

Intelligent automation (IA)

A broad term for combining technologies to automate processes such as accounting. It usually brings together artificial intelligence (AI), business process management (BPM) and robotic process automation (RPA). For finance teams, the aim is fewer manual errors, faster workflows and better information for decisions. IA often pairs AI with RPA so that more complex AP tasks can be automated.

Robotic process automation (RPA)

RPA automates repetitive, rule-based tasks by copying the steps a person would take in existing systems, such as data entry, invoice processing and reconciliations. It doesn't involve AI. RPA works well for simple, routine tasks and can be set up without changing the systems underneath. But it needs ongoing maintenance: whenever a rule, a layout or a process changes, someone has to update it.

Rule-based accounting

A set of rules, maintained by hand, that assigns an account to each transaction as it's imported. It saves time and keeps similar transactions consistent, and it's often built into ERP systems. The drawback is upkeep. Rules need updating whenever regulations or internal accounting practices change. Some companies combine rule-based accounting with AI, using the data to show when rules should change.

Artificial intelligence (AI)

AI is the development of computer systems that can do tasks that normally need human intelligence, like learning, reasoning and solving problems. In AP automation, AI learns from new data without manual updates. It categorises transactions based on what it has learned, spots patterns and anomalies in financial data, and gives finance the data to forecast spend. That means fewer errors, faster processing and more time for work that needs judgement.

Machine learning

The part of AI that learns from examples rather than following rules someone wrote. In AP, a machine learning model studies how invoices were coded before, then suggests coding for new ones. Each time a person corrects a suggestion, the model learns from it, so automation improves the longer it runs.

Line-level capture

Reading every line of an invoice, not just the header (supplier, total, date). Many AP tools read cost invoices at header level only, so the detail of what was bought is lost once the invoice posts. Line-level capture keeps that detail as data you can use to compare supplier prices and forecast spend.

Three-way matching

Checking an invoice against both the purchase order and the goods receipt before it's paid. When all three match, the invoice can move on automatically. When they don't, it goes to someone for review.

E-invoicing and Peppol

An e-invoice is a structured invoice sent in a machine-readable format rather than as a PDF or on paper. Peppol is a widely used network and standard for exchanging e-invoices between businesses. Most companies still receive a mix of e-invoices and PDFs, so AP automation needs to handle both.

Confidence score

A measure of how sure the AI is about each suggestion it makes. High-confidence suggestions can post automatically, and lower-confidence ones go to a person to check. It shows finance why the AI suggested what it did, and where human judgement is needed.

No-touch invoice

An invoice that goes from receipt to posting with no manual edits. The share of no-touch invoices is a common way to measure how well AP automation is working.

Rydoo Intelligence

Rydoo's name for its AI. In Rydoo Accounts Payable, Rydoo Intelligence captures, codes and routes invoices, and shows its reasoning and confidence for every suggestion.

How Rydoo Accounts Payable uses machine learning

Rydoo AP was built with machine learning at its core. Its self-learning AI reads every line of every invoice, whether it's a PDF or a Peppol e-invoice, and understands both the content and the context. It suggests an account, dimensions and VAT code for each line, and every suggestion carries a confidence score. Approval routing follows your own rules. Finance reviews only the exceptions, and the AI learns from each one.

Why the terms matter

AI and machine learning give finance teams more accurate accounting, lower processing costs and better information for decisions. Knowing how they differ from RPA and rule-based automation helps you see what a provider is really offering, and what it'll take to keep it running.

Rydoo AP automates over 40 million invoice lines a year for customers including Norwegian, OBOS and KLP.

See how Rydoo AP handles your invoices