How AI is transforming invoice processing

The challenges of manual invoice processing

The manual processing of invoices is a major challenge for many companies: It is time-consuming, error-prone and ties up valuable human resources. The variety of invoice formats is particularly problematic, making standardized processing difficult. Incorrect assignments and inconsistent data lead to time-consuming correction loops - and as the number of invoices increases, so do the effort and costs.

‍Automation potentialthrough AI

Artificial intelligence can automate key steps in invoice processing - from recognition and amount verification to correct allocation. Human control is retained, while efficiency increases and errors are significantly reduced. The biggest advantage: noticeable cost savings and significantly faster processing.

In addition, the central storage and analysis of invoice data provides new insights: recurring sources of error or conspicuous service providers can be identified and optimized in a targeted manner. In this way, process quality is continuously improved.

Process-oriented solution approach

For technical implementation, we recommend setting up a modular process pipeline: Once the invoice has been received, it is first classified (e.g. invoice yes/no, type of invoice), then the relevant data is extracted and validated against existing databases. AI models are used for classification and generative AI such as ChatGPT for reporting.

The solution approach is open to all technologies and can be flexibly integrated into existing IT landscapes - whether in cloud environments such as AWS or in local databases. Insecure data is forwarded for manual checking. Through continuous retraining, the solution adapts to new invoice types and remains operational in the long term.

‍Project approachand change management

The introduction takes place step by step: from the feasibility study to the profitability analysis and the proof of concept through to generalization and go-live. Successful change management is crucial here - transparent communication, workshops on business logic and the early involvement of all relevant stakeholders promote acceptance and minimize resistance.

‍Practical example: Automated invoice processing in the construction industry

A specific use case from the construction industry shows how AI can significantly simplify and speed up invoice verification for goods deliveries:

When building materials are delivered, the target invoice amount is calculated on the basis of the existing order data - for example, by comparing ordered quantities, units and prices. The incoming actual invoice is then checked automatically: AI models extract relevant information from PDF documents, such as article numbers, quantities and prices. This data is presented in a structured manner, while irrelevant content - such as advertising blocks or footnotes - is hidden.

The extracted information can be transferred directly into existing databases or exported as an Excel file. This creates an end-to-end digital process that reduces manual checks and increases data quality.

‍Otheradvantages of the approach:

• Format independence: Processing of image and PDF invoices, provided they are readable.

• Spam and phishing detection: rules and filters protect against unwanted content.

• Technology openness: Flexible connection to different databases and storage locations.

• Scalability: Can be expanded to include cash management and payment verification with the appropriate technical connection.

‍

‍Conclusionon invoice processing with AI

AI-supported invoice processing is more than just an efficiency booster - it is a strategic lever for digitalization and process optimization. Companies benefit from lower costs, higher data quality and faster processing. At the same time, the solution creates transparency and new analysis potential that goes far beyond mere invoice verification.

Use the potential of AI for your invoice processing. Start with a proof of concept and experience how quickly efficiency and transparency can be increased. ‍Ourtip: For the test phase, we recommend 10-20 sample invoices to cover different cases.

Would you like to find out more or start a pilot project? Contact us for an individual consultation and find out how the solution can be seamlessly integrated into your existing IT landscape.