AI Tools in Accounting and Finance: A Compliance Guide

AI in accounting and finance refers to the use of artificial intelligence for invoice recognition, expense categorisation, payment forecasting, fraud detection, and financial reporting. In a small Lithuanian company, AI is most commonly already embedded in accounting software or banking systems. This means that even if you have never consciously purchased an "AI solution", AI is likely already working in your finance function - and with it come questions of compliance with the EU AI Act. In the financial sector, it is especially important to assess not only the tool itself but also what personal, payroll, or client data it processes.

Accounting and finance are a special area for two reasons. First, they handle a large amount of personal and commercially sensitive data - employee salaries, client accounts, bank statements. Second, an error in financial calculations has direct consequences - it is not a typo in a text, but potentially incorrect VAT or a missed invoice. Therefore, the use of AI in accounting requires more attention than, for example, generating a social media post.

Where AI Is Already Working in Your Accounting, Even If You Don’t Notice

Many managers believe their accounting is "without any AI". In reality, AI functions are already integrated into most modern financial tools. An inventory may reveal several AI-enabled functions across the financial workflow; the number depends on the tools actually used.

Here’s where AI is most commonly found in accounting and finance:

The first practical step is to list all these tools. The best way to do this is by maintaining an AI tools register, which becomes a reference point for all further compliance. Without such a list, it is impossible to assess risks or train employees.

It is worth noting that AI in accounting is rarely a "single big solution". More often, it consists of dozens of small automations embedded in everyday tools: an email filter that recognises invoices; a banking app that groups expenses; a spreadsheet function that "suggests" a formula. Each may seem insignificant on its own, but together they form the actual scope of AI use for which the company is responsible under the EU AI Act.

Is Accounting AI High-Risk Under the EU AI Act?

In most cases - no. Typical accounting AI tools (OCR, categorisation, internal forecasts) fall under the minimal or limited risk category. This means they are not subject to the strict obligations of high-risk systems, but the company must still take appropriate AI literacy measures and assess any applicable transparency duties.

However, there is an important exception. The EU AI Act (Regulation (EU) 2024/1689) classifies AI used for creditworthiness assessment and determining credit scores for natural persons as high-risk. If your company uses an AI solution that automatically assesses whether to grant a client (a natural person) deferred payment, credit, or leasing, such a tool may be high-risk - with correspondingly stricter obligations.

To correctly classify each tool, we recommend reading the overview of AI Act risk categories. A practical rule for small businesses: assess the tool’s intended purpose and the applicable AI Act classification; human review is useful but does not by itself determine the legal risk category. Risk arises when AI automatically makes decisions affecting a natural person without human review.

What GDPR Risks Arise from Using AI in Accounting?

Financial records often contain personal data, for example: employee salaries, executive remuneration, invoices of self-employed clients, bank account numbers. Therefore, the use of AI in accounting is not only an AI Act issue but also a GDPR concern.

Main threats for small businesses:

• Data leakage via external tools. Uploading a bank statement or payroll table to a free version of "ChatGPT" may result in the data being used for model training. This is a common and dangerous mistake.
• International transfers. Many AI services process data outside the EU. It is necessary to check whether the provider ensures a lawful basis for the transfer.
• Retention periods. An AI tool may store uploaded documents longer than allowed by your data retention policy.

These topics - the intersection of AI and personal data - are discussed in detail in the article AI and Personal Data: GDPR Compliance. A brief practical rule: never upload identifiable financial data to AI tools that do not clearly guarantee that your data will not be used for training and will be properly protected.

How to Use AI Tools Safely in Accounting: A Practical Checklist

Safe use of AI in finance does not require expensive solutions - discipline and clear rules are sufficient. Here are concrete steps for a micro-enterprise:

1. Take inventory. List all AI tools operating in the finance function in a register - including "hidden" modules in accounting software.
2. Assign a risk category. For each tool, determine whether it is minimal, limited, or (in the case of creditworthiness) high-risk.
3. Define what can and cannot be uploaded. Clearly specify that payroll, bank statements, and client personal data must not be uploaded to external general AI tools.
4. Keep a human in the decision loop. AI suggests - the accountant confirms. No VAT, payment, or report should be submitted without human review.
5. Check accuracy. AI can "hallucinate" numbers or formulas. Always compare the AI result with the original document.
6. Train employees. Article 4 of the EU AI Act, which regulates AI literacy measures, has applied since 2 February 2025, with supervision and enforcement starting in August 2026. Companies must take measures to support the development of AI literacy among staff and relevant persons, considering their knowledge, experience, training, context, and the people affected. This does not mean a specific or sufficient individual level must be guaranteed. Practical experience shows that standardised training and documentation help companies meet this obligation.
7. Check the provider. Ensure that the AI functions in accounting software or banking apps comply with GDPR and that you have the necessary agreements.

These principles are similar for all service-providing companies - a broader overview can be found in the article on how the EU AI Act applies to service companies.

What Exactly Should a Company Using AI in Finance Have?

A small business can use several practical documents to organise its AI literacy measures: an AI usage policy, an AI tools register, a compliance record under Article 4, and an employee AI guide. It is also recommended to organise AI literacy training with knowledge checks. These documents allow the company to demonstrate that AI is used consciously and controllably in the finance department.

The entire set of documents - AI usage policy, tools register, compliance record, employee AI guide, and AI literacy training with certificates - can be prepared automatically. nebedirbam.lt does this using compliance expert-reviewed templates, without human intervention, for a fixed €149 + VAT (€299) price, tailoring the documents to your company’s situation. For those wanting to start with the smallest step, free AI literacy training is also available, which you can try yourself before choosing the paid team training package. The free path is for one signed-in participant; team training is included in the paid documentation package.

Note: Article 4 of the EU AI Act does not require a specific certificate, a particular document bundle, fixed training hours, an external auditor, or a dedicated AI officer. These are recommended but not mandatory measures.

Common Mistakes When Using AI in Accounting

From practical experience with Lithuanian micro-enterprises, several recurring mistakes emerge in the financial sector:

• "We don’t use AI." Almost always untrue - AI operates in OCR, categorisation, and banking systems. The first step is to acknowledge and inventory it.
• Blind trust in forecasts. Cash flow forecasts are an aid, not a guarantee. Decisions on borrowing or investments must not rely solely on AI.
• Uploading confidential data to free tools. Payroll tables do not belong in an open AI chat window.
• Neglecting training. Buying a tool but not training the accountant to use it safely is a direct violation of Article 4.
• Banning all AI tools. GDPR does not require a blanket ban on AI tools; it is necessary to assess the lawful basis, data minimisation, use approved tools, and implement safeguards.

Those who want to see how this topic fits into the entire compliance system can start with the list of all articles, which includes guides on policies, registers, training, and risk categories.

Conclusion: AI in Finance - An Opportunity with Clear Boundaries

AI tools in accounting and finance offer real benefits for small businesses: less manual work, faster invoice processing, early problem detection. However, these benefits are safe only when the company knows which tools it uses, correctly assesses their risks, protects personal data under GDPR, and leaves the final decision to a human. The EU AI Act does not prohibit or complicate these principles; it requires contextual AI literacy measures, while documentation can help record those measures. For a micro-enterprise, this can be achieved with standardised measures and without major costs, starting with a simple step: an inventory of all AI tools in finance.

This article’s legal information is based on official EU AI Act (Regulation (EU) 2024/1689) Article 4 and implementation timeline data: EU AI Act Article 4 and EU AI Act implementation timeline.