Useful AI is boring
The AI applications that deliver measurable results in a company are unglamorous: reading an invoice and extracting its data, working out which department a request belongs to, finding information inside an archive of contracts.
These are tasks a person does today, that require attention, and that nobody will miss.
How it works in practice
The document enters the flow, the model extracts the fields needed, the system compares them with data it already holds and assigns a confidence level. Above a threshold the data continues by itself; below, it stops and goes to a person.
That threshold is the most important part of the project and is tuned on real data: too high and nothing is automated, too low and errors reach downstream.
The test to run before investing
Before building anything, take a sample of real documents — not clean examples, the real crooked and badly photographed ones — and measure accuracy. It's a week of work and it tells you whether the project makes sense.
If accuracy on your documents isn't good enough, better to know first.
The question about data
It's a fair question and must be settled at the start: where documents go, who keeps them, whether they're used to train models. There are configurations where nothing is retained, and solutions installable on your own systems.
The choice affects cost, so it's made together at design stage, not afterwards.
What to expect
On extracting data from repetitive documents, the time spent drops substantially, and what remains becomes checking rather than typing. The precise number depends on your documents: that's why the initial test matters more than any promise.
Frequently asked questions
Do we need a big project to start?
No. Start with one document type and measure. Extending afterwards is easy; reversing a wrong project isn't.
AI makes mistakes. How do we protect ourselves?
With the confidence threshold, cross-checks against data you already hold, and a decision log. The goal isn't removing people, it's having them step in only where needed.