AI for the admin tasks in your company

Filling in forms, sorting invoices, extracting data from documents, drafting the same kind of letter over and over, copying information from one place to another… Administrative work is essential, but it takes an enormous number of hours that add no direct value to the business. Artificial intelligence is particularly good in this area. Let us look at how it can take the paperwork off your hands.

Administrative work has a peculiarity: nobody asks for it, nobody thanks you for it and it has to be done anyway. It is also the area where automation delivers fastest, because almost everything done there meets the conditions to automate well.

Why this area is the most rewarding

Three reasons. The first is volume: these are tasks that repeat daily. The second is pattern: most are done the same way almost always. The third is that the error is detectable: if an invoice comes out wrong, you see it. That allows automating with more margin than in tasks where a failure goes unnoticed.

There is a fourth, less obvious reason: it is work nobody wants. Automating it generates far less internal resistance than touching processes where people feel their judgement is being questioned.

1. Data entry and transfer

Copying information from one place to another: from the form to the CRM, from the CRM to the spreadsheet, from there to the invoicing software.

It is the most invisible and most expensive work there is. Nobody accounts for it because it happens in two-minute chunks, forty times a day.

What gets built. A flow that reads the source, checks the data makes sense (that the tax number looks like a tax number, that the date is possible), writes it to the destination and only alerts when something does not fit.

The benefit nobody counts. Transcription errors disappear, because there is no transcription. And a badly copied figure is not spotted the day it is copied: it is spotted three weeks later, once it has contaminated other things.

2. Extracting data from documents

Supplier invoices, delivery notes, contracts, case files. They arrive as PDFs and someone has to pull the data out and put it into a system.

What gets built. Reading the document, extracting the fields that matter and moving them into a workable format. Here AI genuinely contributes, because every supplier lays out its invoices its own way and a fixed template breaks on the first new format.

Where to draw the line. Amounts going into the accounts should pass through a validation step. Not because the system fails often, but because the cost of an error there is high and checking a figure takes seconds.

3. Recurring reports

Every Monday someone spends a morning building the same report: downloading data from three places, pasting it into a template, checking it adds up and sending it.

What gets built. The gathering, the calculation, the formatting and the sending. And, if it adds value, a plain-language summary flagging what has shifted since the previous period, which is the only part most people read.

Before automating it, one question. Who reads it and what do they decide with it? Many reports exist out of inertia. Sometimes the right answer is not to automate it: it is to stop producing it.

4. Email management

Sorting, prioritising, writing similar replies and following up on what nobody answered.

What gets built. Sorting by type and urgency, drafts written in your tone, and alerts on anything unanswered for days.

The rule. The AI drafts, you send. The expensive part is not writing the email, it is starting from a blank page. Starting from a reasonable draft cuts most of the time without taking the risk of something poorly judged going out.

5. Preparing repetitive documents

Contracts, quotes, proposals, certificates. Documents that follow a template and are filled with data already sitting in some system.

What gets built. Generated from the template with the data already inserted, ready to review and sign.

One extra. When the document is leaving the organisation, a check can be added that it carries no data that should not go out. It is the same principle we applied in the anonymisation project for Santa Coloma City Council, where reviewing a document by hand took 20 minutes and dropped to 2-3 seconds.

6. Filing and organisation

Naming files consistently, saving them where they belong, tagging them so they can be found later.

It seems minor and it is not: the time lost looking for badly filed documents appears nowhere, but it is there.

What gets built. Renaming to a convention, classification by content and automatic filing in the right folder.

What is best not automated here

• Payments and transfers. Preparing the payment, yes. Executing it without anyone approving, no.
• Delicate communications. A complaint, a grievance, bad news.
• Decisions about people. Nothing related to hiring, appraisal or discipline without human judgement.
• Processes that will change soon. If you are changing ERP next year, wait.

Where to start

With data entry between systems. It has the most volume, requires the least judgement and generates the most silent errors. It is also deterministic, which makes it easy to test: the same input always gives the same output.

Once that works, extracting data from documents. And then email, which saves the most but also needs the most tuning to sound like you.

To put figures on what it is costing you today, the savings calculator works it out in thirty seconds. And if you want a prioritised list of your own processes, that is exactly the free diagnosis.