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YES

As of 13 August 2026, AI can extract data from PDF invoices.

This still needs a person who signs their name to it.

Can you do it?

5 minutesto a draft.

30 minutesto something you’d act on.

Cost, all in£0

Skill neededchat-fluent

Who has to check ityou

What the alternative costsManual entry into a spreadsheet or accounting system is the alternative; no sourced price for that work is provided here.

If this goes wrong: an incorrect supplier, amount or VAT value reaches your records and has to be found and corrected before payment, reconciliation or reporting.

What to actually do

  1. Hand it to a person

    The route this page recommends

    A person who owns the outcome does this end to end, worth it when the failure is dear.

  2. Use a tool built for this

    Second choice

  3. Do it yourself

    The distant third

    A chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.

    How to actually do it

    1. Create a new spreadsheet with columns matching the fields in the prompt, including source_file and source_page.
    2. Gather the PDF invoices you are allowed to process and remove unrelated files, duplicates and documents containing information the chosen service does not need.
    3. Open an approved AI chat or document analysis tool, attach the invoice PDFs, paste the prompt, and ask it to return the extracted rows without inventing missing values.
    4. Copy the returned table into the spreadsheet and keep the source_file and source_page columns beside every row.
    5. Open each invoice PDF and compare the supplier, invoice number, dates, currency, net amount, VAT and gross amount against the extracted row, checking every row marked UNCLEAR or MISSING first.
    6. Recalculate totals and VAT only in the spreadsheet as a separate check, without replacing the values printed on the invoice.
    7. Resolve flagged duplicates, credit notes, unreadable fields and mismatches with the supplier or your finance process before importing the checked rows into accounting software.

    Prompt

    Extract structured data from the attached PDF invoice files. Return one row per invoice in a CSV-style table with these columns: source_file, source_page, supplier_name, supplier_address, invoice_number, invoice_date, due_date, purchase_order_number, currency, net_amount, VAT_amount, gross_amount, payment_details, line_items, and extraction_notes. Preserve values exactly as shown where possible. Do not calculate, guess, correct or combine values. If a field is missing, write MISSING. If a field is unclear, write UNCLEAR and explain why in extraction_notes. Keep invoice numbers, dates, currency codes and decimal places exactly as displayed. For VAT, record the rate or rates and the amount if shown, but do not infer a rate. Put multiple line items in a separate JSON-like list within the line_items cell, including description, quantity, unit_price, VAT_rate and line_total. Flag duplicate-looking invoice numbers, totals that do not appear to add up, unreadable text, credit notes and invoices with more than one VAT rate. Quote the relevant value and page number in extraction_notes for every field that is missing or unclear. Treat the PDFs as confidential and do not include any information that is not present in them.

    Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.

What it gets wrong

  • AI cannot reliably recover text that is missing, obscured or badly scanned.
  • AI cannot know whether an invoice is genuine, approved, duplicated or authorised for payment.
  • AI cannot decide how your organisation should code a purchase, handle a disputed invoice or treat an unusual VAT case.
  • AI can copy a plausible but incorrect value from a complex layout, so checking the source page remains necessary.
  • Uploading invoices can expose supplier, bank and business information unless your organisation has approved the service and handling process.

Even on a YES, the friction has a name: verification cost, private data access and stakes of error.

How we scored this

Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.

AxisScore (0–2)
Output2
Inputs2
Verification1
Liability1
Effort delta2
Total8 / 10

The methodology and its thresholds are published in full.

FAQ

Can ChatGPT read PDF invoices?
Yes, it can extract common invoice fields from many digital and scanned PDFs. It can still misread poor scans or complex layouts, so compare the output with the original invoice before using it.
What information can AI extract from an invoice?
It can usually extract details such as the supplier, invoice number, invoice and due dates, purchase order number, currency, net amount, VAT and gross total. It can also extract line items, but those need closer checking when the invoice has multiple VAT rates or unusual formatting.
Can AI extract invoice data into Excel?
Yes. Ask it for a consistent table or CSV and copy the result into Excel, keeping the source file and page for checking. Do not import the rows into accounting software until amounts, VAT and duplicate invoices have been checked.
Is it safe to upload invoices to AI?
Only use a service approved by your organisation and check how it handles uploaded documents. Invoices can contain supplier names, addresses, bank details and other private business information, so remove unnecessary data or use an approved business workflow where required.

Nearby answers

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Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.

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