Every day, businesses are flooded with information. Invoices, contracts, onboarding forms and compliance records build up quickly. Most of this data is unstructured, making it difficult to sort, search, share and use effectively.
Yet many still rely on manual document handling or outdated optical character recognition (OCR) tools that were never designed to deal with the scale or complexity of modern business.
These old methods slow down work, cause delays and increase the risk of errors. For example, it is common for an invoice to pass through several people for validation and approval. Each step takes time and introduces the chance of mistakes. It also slows cash flow and affects supplier relationships.
Intelligent document processing (IDP) uses artificial intelligence (AI), machine learning and advanced OCR to automate manual data entry from paper-based documents or document images. This allows information to flow directly into digital business processes.
Today’s systems can handle large volumes of unstructured data, extract key fields and validate them against other records.
Initially, IDP adoption was strongest in sectors like finance and insurance, where documents were structured or semi-structured. But more industries are seeing the benefits. In property management, for example, IDP is now used to process lengthy lease agreements, extract specific conditions and flag important clauses automatically.
It has also proven its value in healthcare claims processing. Automating claims helped one organisation capture all clinical documents within 24 hours, cut denied and rejected claims by 50% through real-time validation, and reduce operational costs by up to 50%.
Faster processing and better data controls not only improved compliance and fraud detection but also led to quicker settlements and stronger customer trust.
IDP can recognise and extract important details, even when document formats are not only inconsistent but also multi-language. Information can even be extracted in one language and stored in another. This speeds up workflows and improves compliance by creating a clear record of each step.
This is how IDP works:
- Extracts and organises data to drive automation, combining OCR with AI and machine learning algorithms.
- Scans, reads, categorises and structures meaningful information from a wide range of document types.
- Relies on machine learning, computer vision, cognitive automation, robotic process automation and natural language processing to accelerate document handling.
- Leverages AI and OCR to make information consistent, usable and accessible.
This means even complex contracts or handwritten documents can be processed automatically with a high degree of accuracy.
Moving forward
Many businesses are unsure whether they are ready for IDP, or whether their existing processes are causing problems. A few clear signs include information arriving in different formats that must be retyped manually, long turnaround times for validation or compliance checks, and critical data stuck in silos or on paper, with no easy way to search or analyse it.
Modern IDP solutions focus on automated document extraction to remove these bottlenecks. The goal is to capture information securely and reliably, then push it into the systems that run the business.
One of the biggest misunderstandings is that IDP only involves basic OCR that picks up a few key words. But today’s systems can handle large volumes of unstructured data, extract key fields and validate them against other records.
IDP provides robust encryption, strict access controls and clear audit trails to protect sensitive documents like invoices, contracts and financial records.
It also builds trust through transparency. It shows exactly how each document is processed, tracks exceptions and keeps a full record of what has been captured or flagged. For example, if required information is missing, IDP highlights the gap so teams can follow up or apply rules.
The technology also validates extracted data against other records. If supplier details do not match, IDP can trigger extra checks before processing continues. These safeguards protect data, support compliance and reassure employees that automation still allows for human oversight.
Scaling IDP
There are a few factors that make IDP successful at scale:
- Advances in AI have made it possible to process complex documents without heavy manual intervention.
- Training and change management help employees understand how the technology supports their work.
- Integration with core systems ensures that captured data feeds directly into downstream processes like ERP, payments, or compliance checks.
Efficiency is often the first benefit companies look for, but it is not the only one. Once documents are digitised and structured, businesses can discover trends and insights that were previously hidden.
For instance, one large organisation with hundreds of thousands of client records was able to identify patterns in behaviour and risk factors, which would have been impossible using paper files.
The bottom line is IDP is a ground-breaking component of intelligent automation. The latter transforms the manner in which businesses manage and classify unstructured data.
Tools such as optical character recognition extract text from documents, IDP takes this a step further. It enables software to extract data from complex unstructured formats and in turn make intelligent decisions based on the information gleaned.
Harnessing these capabilities can help companies to process documents more efficiently by uncovering hidden inadequacies and optimising end-to-end processes.
Share