From PDF invoices to a spreadsheet with AI: what can be automated?

Start with the spreadsheet you need

Define columns before choosing a tool: supplier, reference, date, currency, total and, if needed, line items. Agree the date format and what happens when a value does not appear in the document.

Do not ask the system to fill gaps by guessing. A blank field marked for review is easier to manage than a plausible but incorrect value. Keep a file reference for every exported row.

Reading text and extracting fields are different steps

OCR turns text in an image into usable text, while extraction organizes information into fields. Google Document AI documentation describes tools for key-value pairs, tables and fields defined for a particular use case.

This does not mean every invoice will be read correctly. A tilted scan, cropped photograph or unusual table can affect the result. Test documents your business actually receives, rather than relying on one clean sample.

Put checks between extraction and export

• Are required fields present?
• Are dates and currencies in the expected format?
• Are comparable totals consistent?
• Has the document already been processed?
• Can the row be traced back to the original invoice?

These are suggested operational checks. They do not establish a document’s tax validity or authorize payment. Exceptions must reach the responsible person.

Organize a pilot

Choose samples from several sources with different quality levels. Prepare correct outputs manually for comparison. Count correct fields, missing values and correction time; do not judge the system only by whether it creates a spreadsheet.

Decide who can access documents, where they are processed and how long they are retained. Use approved test material and review provider settings before sending real documents into the system.

Decide when to connect other applications

If the checked output is useful and volume justifies the work, connect the export to an internal system. Imports need duplicate-handling rules and a correction path. Start with a step that prepares information for a colleague.

AI document processing covers reading and the agreed checks. Workflow automation can add file collection, notifications and export. Keep the point where a person approves use of the data explicit.