Operations

Stop Paying Someone to Copy and Paste: Automating Data Entry

How AI reads invoices, receipts and delivery paperwork, checks its own work, and fills your software, with a person reviewing anything it flags.

By JBthaGREAT4 min read
A tall stack of paper documents marked with colorful sticky tabs
Photo: Tanja Tepavac on Unsplash

Somewhere in your business, a person is reading a document and typing what it says into another program. It might be invoices, receipts, purchase orders, bills of lading, delivery receipts or intake forms. They do it every day, and you pay for every hour of it.

AI can do the first pass for you. It reads the document, pulls out the details, checks them against your records and fills in your software. A person only looks at the items it flags. Here's how that works, where it goes wrong, and how to start without risking your books.

How AI data entry works, step by step

  1. Documents come in. By email, a scanner, an upload, or a photo from a phone.
  2. The AI reads them. It pulls out the details you care about: vendor, date, amount, invoice number, order number, line items.
  3. It checks its own work. Do the line items add up to the total? Does the order number match an open order? Is this invoice a duplicate?
  4. A person reviews what's flagged. Anything the AI isn't sure about, or anything that fails a check, goes to a review list.
  5. Approved details go into your software. Your accounting software, your dispatch system or your inventory system, wherever they belong.
The AI does the typing. A person checks what it flags.

Two examples from very different businesses

Different businesses, same pattern. A person stops typing and starts checking.

What makes it work well

Start with one kind of document

Pick the one that eats the most hours, such as vendor invoices. Get that working before adding the next.

Connect to as few systems as possible

The AI builder Aayush Jain writes that the cheapest first project "integrates with one or at most two systems that have good APIs." An API is the door one piece of software uses to talk to another. Fewer doors, less work, lower price.

Keep a person in the loop

Jain describes two versions of the same assistant. In the cheaper one, a person "catches the bad cases." The more expensive one is needed when documents go straight into your accounting software with nobody reviewing them, and he says the cost difference "can be 2x." For a first project, a review step is the sensible choice.

Test on your real paperwork

The AI builder SuperDupr builds and tests on "actual invoices," not demo files. Ask any builder to do the same. Hand over a stack of your real documents, including the blurry, crumpled and handwritten ones.

Where it goes wrong

  • Bad scans and photos. Blurry, dark or cut-off images get misread. A good setup flags them instead of guessing.
  • Handwriting. It's harder to read than print. A good setup sends unclear handwriting to a person.
  • New layouts. A new vendor with an unusual invoice layout may need a few corrections before the AI handles it well.
  • No checks. An assistant that types without checking totals and duplicates will move mistakes into your books faster. Insist on checks.

Do the math with your own numbers

The builder Naurra.ai suggests a simple formula: hours per week, times what an hour costs you, times 52.

Put in your own numbers, then compare the result with what an AI build costs. My guide to what a custom AI build costs shows the published price ranges.

How to get started

  1. Pick the document type that takes the most hours.
  2. Gather real examples of it, including the messy ones.
  3. Write down which details you need from each one, and where they go.
  4. Write down the checks a careful employee does today.

Send me those four things. I'll read them and send you a custom quote. No sales calls.

Sources

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