Accounting firms have an unusually good starting position with AI. Most of the work repeats, the input is a document, and the rules are written down. Payback shows up sooner here than in most industries.

This article walks through four processes in the order worth implementing them. For each one: the typical time saving, the rough cost of implementation, and the point where a person has to stay in the loop.

Why this particular order

The order does not follow the size of the saving. The first process comes first because it is cheap, live within two to three weeks, and it shows the team that this works. The biggest item comes second: it needs the routine from the first project, and it needs clean data.

One shared figure runs through the whole article: the internal hourly cost. Salary, contributions and overheads together typically sit between 15 and 22 euros for an accounting role in the region. We use 18 euros throughout. You can work out your own in a minute, and the calculator gives you the order of magnitude too.

One caveat: the figures below are typical industry ranges, not promises. Your own measurements apply to your firm, and two weeks of measuring is enough.

The four processes, in order

1. Chasing missing documents

Every month starts the same way: who has not sent what. Today that means a manual list, then emails, then phone calls, and someone keeping the gaps in their head.

What a machine can do: compare received documents against expected ones, send reminders client by client, watch deadlines, and deliver a summary of everything outstanding each morning.

Typical effect: 60–80% of the time spent chasing disappears. In a firm of 5–8 people that is 10–15 hours a month, or 180 to 270 euros.

Implementation: 2–3 weeks, and it is the cheapest of the four.

What to watch: the tone of a reminder is a client relationship, not a technical question. Write a template, and keep an exception list for clients a person should still contact personally.

2. Data extraction from incoming invoices, with a posting suggestion

This is the big item. The supplier, document number, date of supply, net amount, VAT rate and line items can all be read from the image of an invoice. The system then proposes a posting based on previous bookkeeping. The accountant no longer types, they check and approve.

Let us put numbers on it. A firm processes 1,200 incoming invoices a month, and entering one by hand takes 5 minutes. That is 100 hours a month. Extraction plus the suggestion typically cuts 50–60% of that, so settle on 55 hours. At an internal cost of 18 euros an hour, that is 990 euros a month. If implementation costs 4,000 euros, payback lands at around four months.

What to watch: recognition accuracy in the first month is typically 85 to 95%, and improves as patterns are learned. The key is not accuracy itself but making sure uncertain items go into a separate queue rather than disappearing into the approved pile. Ask for a confidence indicator on every line.

Implementation: 6–10 weeks, because tidying up formats and the supplier master data also takes time.

3. Internal document and knowledge search

The third process is the dullest of the four, which is exactly why it is good. The system searches the firm’s own material: internal policy, earlier written opinions, client folders, extracts from legislation, questions already answered by email. A colleague asks in one sentence and the system answers with the source named.

Typical effect: an accountant spends 20–40 minutes a day searching and asking colleagues. Half of that realistically disappears: 4–7 hours per person per month. At six people that is 25–40 hours a month, worth 450 to 720 euros.

Implementation: 3–5 weeks if the documents are in one place. If they are not, that is the first half of the project.

What to watch: a search tool only knows what has been written down. If the knowledge sits in people’s heads, write it down first: useful work in its own right. Permissions must be inherited: if someone cannot see a client folder, search must not show it either.

4. Suggested replies to client emails

A large share of incoming questions repeat: filing deadlines, what to send, where a matter stands, what data the authority wants. The system classifies the message, drafts a reply from your own material, and the accountant reviews, corrects and sends it.

Typical effect: response times get shorter, and writing time on routine messages drops by 30–50%. Reviewing one draft takes ten to forty seconds, so most of the saving survives.

Implementation: 4–6 weeks.

What to watch: this is the riskiest of the four, because the output goes to a client. There is no automatic sending. The machine suggests, a person sends, and that part is not negotiable.

What it adds up to

Taken together, the four typically cut into a monthly workload of roughly 90–130 hours in a firm of 5–8 people, and total implementation lands between 7,000 and 12,000 euros. Overall payback is usually 5–9 months if you roll them out one after another.

Process	Typical saving	Implementation	Risk
Chasing documents	10–15 hours a month	2–3 weeks	low
Invoice extraction	50–60 hours a month	6–10 weeks	medium
Internal search	25–40 hours a month	3–5 weeks	low
Suggested replies	8–14 hours a month	4–6 weeks	higher

These are ranges, and the top end requires clean data. If supplier master data is messy or folders are scattered, the top end will not materialise.

In an accounting firm the question is not whether a machine can do the books. The question is what no longer has to be retyped by hand.

What not to automate, and where a person stays in the loop

Accounting is a regulated profession and mistakes carry a price. Four points where the machine stops and a person decides.

• Filing with the authorities. Final approval of a return, report or submission stays with a person. The machine prepares, a person presses the button.
• Posting unusual or disputed items. A suggestion on routine items is fine. An unusual case, a borderline case or a classification question is professional judgement, not pattern recognition.
• Tax advice and written opinions. When a client asks what they should do, there is liability behind the answer. The machine can draft it, a person signs it.
• Payroll exceptions. An ordinary month can be automated. Sick pay, severance, deductions and legal disputes cannot.

Two rules that work every time. Keep a log of what the system suggested and who approved it, because you will need it after the fact. And set a value threshold above which a second pair of eyes is mandatory, typically 500 to 2,000 euros depending on firm size.

Data protection and the AI Act, briefly

An accounting firm handles other people’s data, which means stricter rules than in an average company. Sort out three things before the pilot.

1. Where the processing happens. Processing in the EU, an account that does not train on your data, a written data processing agreement. Client data does not belong in a free consumer account.
2. Who sees what. The AI tool’s permissions must not be broader than a colleague’s. Inherited access per client folder is the right baseline.
3. AI literacy. Under Article 4 of the EU AI Act, staff must have an adequate level of AI literacy. A documented internal training session twice a year satisfies it; a separate article on the blog has the details.

How to start

Do not launch all four at once. Measure for two weeks: how many invoices arrive, how long one entry takes, how much time goes on chasing documents. Then start with document chasing: it is live within three weeks, and after that the team stops arguing in principle and starts looking at numbers.

If you want the order of magnitude in advance, our prices are published, so a decision does not need a round of quote requests. At the end of the audit you get a sequence, including which process to leave alone this year.