Short answer: business process automation is when a system, not a person, does repetitive computer work: moving data, entering documents, replying to customers, producing reports. AI automation, which people also call "AI process automation", adds what older systems couldn't do: it understands messy information. A PDF invoice, a free-form email, a photo or a scanned document. That's why today you can automate jobs that a few years ago couldn't run without a person.
Below: how AI automation differs from the ordinary kind, what jobs it already does in real companies (with the numbers from our projects), what a project looks like from the first conversation to launch, and when automating isn't worth it at all.
Ordinary automation vs AI: where the line is
Ordinary automation runs on rules: "when a form is filled in, create a record in the CRM." Zapier, Make, n8n or Excel macros have done this for years. They're fast and cheap, but they have one weakness: they only work with tidy data. They move a field to a field. When an invoice arrives from a new supplier with a different layout, the rule stops or, worse, quietly enters the wrong number.
AI reads the way a person reads. It doesn't matter where on the invoice the amount or the VAT is written: it understands who the supplier is, what the amount is and which order it belongs to. And when it's unclear, it doesn't guess, it hands it to a person.
| Rule-based automation | AI automation | |
|---|---|---|
| What data it understands | Only tidy data: form fields, tables | Also free text, PDFs, photos, emails |
| What happens with a new layout | Stops or makes mistakes | Reads it like a person, hands unclear cases to a person |
| Typical example | From a website form to the CRM | From an email with an attached invoice to the accounting software |
| Where it's strong | Simple steps that are always the same | Work that requires reading and deciding |
In practice the two work best together: rules where rules are enough, and AI where something has to be read or decided. There's no point paying for AI where a simple rule will do.
What AI automation already does in real companies
Instead of writing theory, I'll show you our projects. The numbers are one month's results from the case studies:
| Company | What the system does | Saved per month |
|---|---|---|
| US shopping intermediary | Issues ~6,000 invoices and matches ~5,000 payments against the bank statement | ~300 h |
| Auto parts company | ~8,000 price checks across 6 platforms, changes ~800 prices on its own | ~400 h |
| Accounting firm | Collects ~9,000 client invoices from email, WhatsApp and Telegram and matches ~18,000 bank statement lines | ~400 h |
| Pupsik LT (online store) | Creates ~1,000 product listings in 4 languages from a supplier's Excel row and a photo | ~300 h |
| Freight forwarding company | Scores ~15,000 freight exchange listings and sends the manager ~200 good loads with a price | ~150 h |
| Ultimate Logistics | Finds companies in public registers and sends ~3,000 personalized emails | ~150 h |
| Hospitality group | Generates ~300 contracts and orders, tracks document expiry | ~100 h |
In total these seven systems do about 1,800 hours of work every month. That's roughly ten full-time jobs.
And notice one thing: none of them is a "conversation with AI". Most work quietly in the background: reading emails, moving data between systems, checking statements. That's where most of the hours are. I explained the difference between a system like that and a chatbot in a separate article.
What an automation project looks like
Four steps, without a big IT project:
- 1. One process. Not "let's automate everything", but one job that repeats most often and has clear rules. I wrote up how to pick it here: which work is worth automating first.
- 2. A pilot on your data. In 2 weeks, on your real data, we show how much the system actually saves. If we don't hit the agreed target, we refund the money.
- 3. Launch where you already work. The system works in your mailbox, spreadsheets, accounting software or online store. Employees don't need to learn a new program. Important actions, such as an email to a customer, a person approves with one button, and every action the system takes is written to a log.
- 4. Maintenance. Processes are alive: prices, suppliers and software change. A system nobody maintains starts making mistakes after a few months. What that means in practice: AI agent maintenance.
What it costs
On the Lithuanian market, automating a single process usually costs from a few hundred to a few thousand euros, plus monthly maintenance. I put all the market prices in the pricing article.
We calculate differently: the build price depends on scope, and for the work you pay up to $7 for every hour the AI did in place of a person. The same hour done by a person costs a US employer $46.89, wages plus benefits (BLS, June 2026). The monthly minimum is $300. So automation starts to clearly pay off from about 20 hours of work a month. What that looks like with your numbers is shown by the ROI calculator.
When automating isn't worth it
I'll tell you the other side too, because it matters:
- There's too little work. If a process takes a few hours a month, building it won't pay off. Then a ready-made tool is better, or nothing.
- The process changes every week. Sort out the way you do things with people first, then automate.
- The decision needs negotiation or empathy. An angry customer and complicated negotiations stay with a person.
- It's unclear what a correct result is. If you can't say it, the system can't either.
And sometimes what you already have is enough: is plain ChatGPT enough for you. If you're wondering what automation means for your team, I wrote about it here: will AI replace employees.
Questions about business process automation
What is business process automation?
It is when a system, not a person, does repetitive computer work: moving data between systems, entering documents, replying to customers, producing reports. People are left with decisions, negotiations and unusual cases.
How is AI automation different from ordinary automation?
Ordinary automation runs on rules and only works with tidy data, for example moving form fields into a CRM. AI automation also understands messy information: PDF invoices, free-form emails, photos. That is why it takes over jobs that used to need a person to read and decide.
Which business processes are worth automating first?
The ones that repeat most often, follow clear rules and where it is clear when the result is correct. Most often that is invoice entry, bank statement matching, answers to repeated customer questions, sorting inquiries and filling in documents. More here: which work is worth automating first.
Do we need to change our software to automate?
Usually not. The system connects to what you already use: email, spreadsheets, accounting software, CRM or online store. Employees don't need to learn a new program, and they approve important actions with one button.
How long does business process automation take?
We show the benefit in a 2-week pilot on your real data, and if we don't hit the agreed target, we refund the money. The length of a full rollout depends on how many systems have to be connected: one process with one system launches faster than several processes with several systems.