Sending and downloading invoices is solved with classic integrations. AI helps at the edges: documents arriving outside the system, matching and suggestions for the accountant.
Since e-invoicing became general among Romanian companies, every B2B invoice goes through the tax authority’s system (ANAF). For many small businesses this meant an extra step every day: issue the invoice in the invoicing software, upload it, wait for validation, download the invoices received. The natural question is what can be automated and where AI has a role. The honest answer: most of it is solved with ordinary integrations, and AI helps in a few well-chosen places. This article is written on 5 March 2026; tax rules change often, so check the current version with your accountant or on the ANAF website.
How the system works, in brief
RO e-Factura is the national e-invoicing system run by ANAF. According to the ANAF guide, the obligation for invoices between taxable persons established in Romania was introduced in two stages (from 1 January 2024, reporting invoices in the system, and from 1 July 2024, sending invoices to the buyer through the system), on the basis of a derogation approved for Romania by the Council of the EU. Individuals and some other situations have separate rules, which have evolved over time.
The basics:
- Format: the electronic invoice is an XML file built to the European standard EN 16931 and the national RO_CIUS rules. The original is the XML file bearing the Ministry of Finance’s electronic seal, not a PDF.
- Access: the company must be registered in the SPV (ANAF’s Virtual Private Space).
- Submission: it can be done by manual upload with the Ministry of Finance’s free application, or by your own software through web services (an API), authenticated using the OAuth protocol.
- Deadline: the 2023 ANAF guide gives 5 working days from the invoice date. The deadline and penalties have been adjusted several times, so confirm the current values.
- Penalties: the guide provides for fines for late submission, which vary with the size of the taxpayer, and a fine for a buyer who records a B2B invoice received outside the system. You will find the exact amounts in the guide and in the acts currently in force.
- Invoices received: these are downloaded from the system. The guide states that valid files stay available for download for a limited period, so a regular download routine matters.
What can be automated without AI
Most of it is plumbing work, where a classic integration is safer than a language model:
- generating the XML file from data in the invoicing software or ERP;
- automatic submission through the API and collecting the validation response;
- periodic download of invoices received and storing them in a fixed place;
- alerts when an invoice has been rejected, with the reason, so a person can fix it quickly;
- automatically sending monthly sets to the accountant, with a record of what was submitted and what was not.
Reliability matters here, not intelligence. A deterministic, tested process that tells you what happened beats a “clever” solution that is sometimes wrong.
Where AI helps
AI becomes useful at the ends of the process, where irregular documents come in:
- Invoices that do not arrive through the system: from suppliers abroad, receipts, statements, scanned documents or photos. A model can extract the supplier, number, date, amounts and line items, and a person verifies.
- Matching with orders: comparing an incoming invoice with the order and goods receipt, flagging differences.
- Classification suggestions: an expense category or cost centre suggested from history and approved by the accountant.
- Drafting explanations: a message to the supplier when the invoice does not match the order, or an internal note for an exception.
- Reading emails with attached invoices and routing them to the right person.
Where AI has no place
- VAT calculation and tax classification. These are done by rules, in the accounting software, and responsibility lies with the company and its accountant.
- XML file compliance. Validation is done by the system and the official validators. A model that “generates XML” can produce a file that looks right and gets rejected.
- Decisions without a person: automatic posting to the ledger without review, automatic payment of an invoice.
- Sensitive customer data on an unassessed tool. If you send invoices to an AI service, apply the same data protection rules as anywhere else; we covered them in the article on GDPR.
A realistic flow, step by step
A hypothetical example, for a small services company:
- The invoicing software generates the invoice and sends it through the API to the ANAF system.
- The validation response is recorded; if the invoice was rejected, an alert appears with the reason.
- Every day, a process downloads incoming invoices and archives them.
- Documents that do not arrive through the system are read by an extraction model and placed in a review queue.
- The accountant sees a list of suggestions (supplier, amounts, category), corrects them and approves.
- At month end, the set is exported and sent automatically to the accountant, with a record of exceptions.
None of this requires AI to make tax decisions. It prepares; the person decides.
How to choose
If your invoicing software already integrates with RO e-Factura, you probably need nothing custom for submission. Spend the effort where you lose time: receiving, checking and classifying documents. Start with a month of real documents, measure how much of the extraction comes out right and how much needs correction, then decide.
If you want to see what can be connected in your business, ME Digital provides AI implementation and custom software for flows like this; write to us on the contact page. For how the tax rules apply to your case, consult your accountant or a tax adviser.