Why Artificial Intelligence Remains Indispensable in the Era of E-Invoicing

18.06.2025

Topic: AI and Machine Learning | E-Invoicing

In the world of accounts payable automation, document reading has always played a central role—but also one particularly prone to errors. Manual data entry, OCR-based extraction, and rule-based logics often reach their limits, especially when dealing with unstructured or inconsistent documents. This is exactly where Artificial Intelligence (AI)—particularly in the form of Generative AI (GenAI) and Large Language Models (LLMs)—can unleash its full potential. But what happens when e-invoicing becomes mandatory, making invoices machine-readable by default? Does this render AI obsolete?

The answer is a resounding no—and here’s why.

E-Invoicing: Progress with Limitations

While more and more countries are making e-invoicing mandatory—such as Italy, France, Poland, Belgium, and Germany—these regulations are far from comprehensive. In Germany, for instance, B2C invoices (those sent to consumers) are currently exempt. Microtransactions under €250 also fall outside the e-invoicing mandate. Beyond Europe, many countries neither require e-invoices nor have plans to introduce such legislation in the near future. In these cases, traditional invoice formats—whether PDFs or scanned documents—remain the norm. And here, AI-powered document capture is still essential.

Invoice Processing Is More Than Just “Reading”

Even when an invoice is fully machine-readable, data extraction is only the first step. In practice, key information often isn’t included directly on the invoice—data necessary for proper accounting classification, budget assignment, or integration into complex procurement workflows. This is where contextual knowledge becomes crucial: What project was the service performed for? Which cost center is responsible? How should it be handled in the ledger? These are precisely the kinds of tasks that AI excels at. LLMs can draw from internal company data, historical patterns, and external context to generate intelligent, automated, and adaptive recommendations.

P2P Is More Than Just Invoices

There’s another important aspect: the Purchase-to-Pay (P2P) process involves a wide variety of document types beyond just invoices. Order confirmations, delivery notes, remittance advices, and credit memos—many of these documents are not standardized and fall outside e-invoicing requirements. Once again, the “capture” step—intelligently extracting and interpreting data—remains essential. AI systems that can adapt to diverse document types and continuously learn provide major efficiency gains in these areas as well.

Conclusion: Stronger Together—E-Invoicing and AI

The rise of e-invoicing marks a significant milestone in the journey toward digitalization and automation. It eliminates many manual error sources and accelerates data exchange. But it does not replace the holistic, intelligent approach that AI brings to invoice processing. In fact, these two technologies complement each other perfectly: e-invoicing creates a clean data foundation, while AI ensures that the remainder of the process is handled intelligently, contextually, and autonomously.

The shared goal remains the same: to automate financial operations—like invoice processing—as much as possible. Employees should be freed from repetitive tasks to focus on more strategic and value-creating work. In this vision, AI plays a critical role—even (and especially) in an e-invoicing world.