Find out how intelligent document processing can revolutionize your processes and what advantages this evolution brings in times of scarce resources and shrinking IT budgets.
Input management has changed fundamentally over the last few decades. What once began with paper documents and manual processes is now a digital, AI-supported solution. In this blog article, we take a look at the evolution of document processing in input management and show how artificial intelligence (AI) is revolutionizing the way companies process data and documents.
The beginning: paper and manual processing
In the early days of office work, input management consisted mainly of paper documents. Invoices, orders, contracts and other business documents were received in physical form and manually recorded, sorted and processed. This process was not only time-consuming, but also prone to errors. Companies relied on manual input, which led to delayed response times and an increased error rate.
The term "inbox" played a central role in this era. In the office world, the inbox referred to a physical container in which incoming documents were collected before being processed or forwarded.
In summary, traditional input management was characterized by physical documents and manual processes that were both time-consuming and error-prone. The inbox symbolizes the starting point of this "old" world of office organization.
The transition to digitization: scanning and OCR technologyOCR (Optical Character Recognition) technology automates the scanning of printed documents... More
As digitization progressed, companies began to scan paper documents and create digital copies. A decisive milestone was the development of Optical Character Recognition (OCR). This technology made it possible to identify text on scanned documents and convert it into machine-readable text. However, the real efficiency gain of OCR was not in the mere conversion of text, but in the ability to process it automatically, search it and integrate it into digital workflows. This significantly reduced manual effort and accelerated document processing.
But OCR was only the first step. Challenges still remained, such as the high error rate with poorly formatted documents or handwritten notes. Nevertheless, this technology laid the foundation for modern, digital input management and paved the way for further innovations.
Automation and workflow as an entry point for digital transformation
As time went on, companies expanded their digital systems to further minimize their manual work. With the introduction of workflow management systems and automated processes, companies were able to make the entire lifecycle of a document, from capture to archiving, more efficient.
These systems made it possible not only to automatically categorize and tag documents, but also to efficiently forward them to the right departments. A key benefit was the drastic reduction in processing time and error rates, as human intervention was minimized and processes were automated. Companies were not only able to respond more quickly to inquiries, but also optimize their internal processes. For example, by stating the invoice number and bank details, a document can be sent to the accounting department as an "invoice". If the document contains a supplier and part number, it can be forwarded as information to the purchasing and production planning departments.
Examples
A key entry point for the digital transformation of companies is the automation of processes and the introduction of intelligent workflows. Even simple automation measures can reduce manual work steps, minimize sources of error and make workflows more efficient. A good example of this is the automated processing of incoming documents.
For example, a system can automatically recognize that a document is an invoice based on specific characteristics - such as an invoice number and bank details. In such a case, the document is forwarded directly to the accounting department without further action. This not only saves time and resources, but also speeds up the entire accounting process.
Another example is the automatic recognition of supplier or part numbers in a document. This information indicates that it is a message that is relevant for purchasing or production planning. The system can classify the document accordingly and forward it to the relevant departments. This ensures that important information reaches the right place without delay.
Such automated processes form the basis for a systematic digital transformation, as they help to process information efficiently and improve communication between departments. Even with simple, clearly defined rules, a company can take the first steps towards a digitalized way of working - with tangible benefits in day-to-day business.
The process began with document separation, in which different document types were distinguished from one another using intelligent algorithms. In the classification process, the documents were then sorted according to predefined criteria, which enabled them to be assigned quickly and precisely. Data was then extracted by automatically capturing relevant information such as names, addresses or contract data and processing it in a structured form. Finally, verification was carried out by a person to ensure that all information was extracted correctly and that no errors remained in the documents. A practical example is used below to illustrate how this process works in practice.
The rise of AI in input management
As digitalization and automation progress, the complexity of processed data is increasing. While traditional systems relied on predefined rules and patterns, artificial intelligence (AI) is ushering in a new era in input management.
AI-based systems, such as Buildsimple , are able to understand, analyze and automatically categorize documents - regardless of format or source. Using advanced technologies such as Natural Language Processing (NLP) and Machine Learning (ML), these systems can process text, images and even handwritten notes.
Figure 1: Buildsimple as an IDP platform | isr.de
A clear example of this is the automatic extraction of data from invoices, contracts or order forms. Whereas employees used to check each document manually and extract relevant information, AI systems now perform these tasks automatically and in real time - faster and more accurately. This saves time and resources, particularly in specialist departments and the mailroom, and allows employees to focus on value-adding activities.
The importance of dark processing
A key aspect in this context is dark processing, in which processes are fully automated so that no manual intervention is required. This reduces the workload for an IT manager, as less manual interface maintenance and support work is required. This not only increases efficiency, but also customer satisfaction thanks to faster processing times. One example is the entire insurance application process - from the online application to the finished policy - which is processed without the intervention of a clerk. Dark processing primarily takes over routine tasks that do not require complex decision-making and thus relieves the IT infrastructure.
A typical example of dark processing is automated invoice processing. Here, incoming invoices are recorded, checked and released for payment without human intervention. The system automatically reads the relevant information, such as invoice number, amount, bank details and due date, compares it with purchase orders or contracts and initiates payment as soon as all criteria are met. This type of automation not only saves time, but also reduces the error rate that can occur with manual entry or checking.
This automation relieves employees of routine tasks and allows them to concentrate on more complex, value-adding activities. Dark processing therefore not only helps to increase efficiency, but also to improve the job satisfaction of employees, who no longer have to deal with repetitive tasks.
AI in use: between efficiency and responsibility
There are critical voices regarding the increasing use of AI in the corporate world, particularly with regard to the fear that automated processes could lead to inadequately reviewed decisions.
An incident in 2024, in which Brian Thompson, CEO of UnitedHealthcare, was tragically shot dead on the street(Brian Thompson: What is known about the case of the US insurance boss who was shot dead | ZEIT ONLINE), has triggered a broad discussion and the practices of insurance companies. In the public debate, questions about the role of algorithms and artificial intelligence (AI) also came into play: How much decision-making power lies in automated systems, and how transparent and fair are their decisions? The incident thus highlights the fundamental tension between automation and human control in an industry whose decisions can have existential consequences for individuals.
In property insurance, which processes a large number of claims every day, AI-based systems offer a promising opportunity to increase efficiency. Claims notifications - especially for smaller amounts of up to €300-500, for example - could be processed much faster with well-integrated dark processing and AI support. The verification processes, such as validating the policy, checking special regulations or clarifying the complete claims information, could be carried out automatically and precisely for such smaller amounts. This significantly reduces personnel costs for manual checks without compromising the quality of decision-making.
It is important that the integrity of the system remains guaranteed. The AI technologies used must be transparent, comprehensible and reliable in order to ensure customer trust in the (insurance) company. With automated processes in particular, it is crucial that customers always have the feeling that their concerns are being taken seriously, treated correctly and fairly. The use of AI must never lead to a lack of transparency or communication; on the contrary, it should help to improve customer service and make processes more efficient.
An outlook: The future of input management
The future of input management will be significantly influenced by even more advanced technologies. In addition to AI , blockchain, cloud computing and robotic process automation (RPA) could also play an increasingly important role. These technologies offer enormous potential to further automate and optimize input management so that companies can make their processes even more efficient and flexible.
However, the decisive factor remains: the evolution of input management has paved the way for a fully digitalized and automated future. Companies that integrate these technologies at an early stage will not only increase their efficiency, but also gain a competitive edge and position themselves as pioneers of digital transformation.
Conclusion: The ongoing evolution of document processing
The evolution of document processing, from manual processing of paper-based documents to AI-powered, fully digitized solutions, shows an impressive advancement in efficiency and accuracy. Technologies such as OCR and AI enable automated document processing that reduces errors and speeds up workflows. Despite these advances, it remains important to maintain ethical standards and human oversight to minimize potential risks. Future innovations such as blockchain and RPA will further revolutionize document processing and give companies new competitive advantages.
Cihan Klingsporn
Senior Account & Marketing Managerin
Business Process Automation
cihan.klingsporn@isr.de
+49(0)151 422 05 471
