AI-based process automation with Intelligent Document Processing (IDP)

AI-based process automation significantly reduces manual effort by automatically recognising, processing and integrating documents into existing systems. This speeds up workflows, minimises error-prone steps and makes processes more efficient overall. At the same time, data quality improves as information is processed in a structured and consistent manner. Companies thus benefit from time and cost savings, as well as scalable, end-to-end workflows.

Recurring, rule-based and document-intensive processes involving the processing of large volumes of data are particularly well suited to automation. These primarily include tasks such as capturing, checking and forwarding information from documents or emails. The use of AI automates these manual and often time-consuming steps, thereby reducing errors and speeding up processes. Employees are not replaced in the process, but rather have specific tasks taken off their hands, allowing them to focus more on complex, value-adding tasks.

The AI processes documents based on their text content, regardless of layout, format or language, and can also recognise unstructured content and handwriting. It extracts relevant data based on context, can enrich this data, and flags missing or uncertain information for targeted review. In addition, data is validated to identify errors at an early stage and improve quality in the long term. In the event of discrepancies or uncertainties, the document can be forwarded directly to the relevant case handler, ensuring approval before further processing.

Automated document processes can be seamlessly integrated into existing IT systems via interfaces. The extracted and processed data can be transferred directly to systems such as ERP, DMS, TMS or – in the public sector – to specialist systems. In this way, information is further processed, archived or transferred to downstream processes without any media breaks. This results in end-to-end, automated workflows from document capture through to final processing.

When it comes to AI-based document processing, particular emphasis should be placed on data protection and data security. It is important that the solution operates in compliance with the GDPR, ideally meets certified security standards (e.g. SOC 1 Type 2) and reliably protects sensitive documents. It is also advantageous to use a proprietary, closed AI system that does not involve third-party providers and does not mix with external data. This ensures that processing remains fully controllable and data sovereignty is guaranteed at all times.

Data security plays a central role in AI-based document processing, particularly when it comes to sensitive corporate and administrative data. It is crucial that the solution operates in compliance with the GDPR, meets high security standards and holds relevant certifications such as SOC 1 Type 2. By using a proprietary, self-contained AI system without the involvement of external third-party providers, the processing remains fully controllable and there is no mixing with external data. This ensures that documents and information are processed in a secure and traceable manner at all times.

Der Automatisierungsgrad hängt stark vom jeweiligen Prozess, der Datenqualität und der Struktur der Dokumente ab. In klar definierten, dokumentenbasierten Prozessen kann ein sehr hoher Automatisierungsgrad erreicht werden – in vielen Fällen bis zu 99 % der manuellen Verarbeitung. Besonders standardisierte und wiederkehrende Abläufe lassen sich nahezu vollständig automatisieren. In komplexeren oder uneindeutigen Fällen bleibt eine gezielte manuelle Prüfung sinnvoll, um Qualität und Kontrolle sicherzustellen. Wie hoch das Automatisierungspotenzial in Ihren Prozessen ist, lässt sich am besten anhand konkreter Anwendungsfälle bewerten.