Unstructured documents refer to documents without a pre-defined layout, which have a high structural and semantic variability, such as contracts and emails. Although such documents are highly prevalent in an organization’s routine transactions, enterprises have largely relied on extracting information from them via manual processes, which are time-consuming, error-prone, and inscrutable.

Intelligent Document Processing (IDP) is an AI-enabled document-processing approach that helps automate data extraction from such non-templatized documents. It has enabled enterprises to achieve reasonable levels of accuracy and Straight-Through Processing (STP) rates in processing semi-structured documents such as invoices and purchase order bills. In the last few years, IDP vendors have been focusing on processing unstructured documents that were largely untouched earlier. IDP construct for unstructured documents is different from semi-structured documents in terms of document complexity, underlying technology, and expected outcomes. Therefore, it is essential for an enterprise buyer to understand the key use cases and technology capabilities of an IDP solution for unstructured documents to choose the best-fit provider and align stakeholders’ expectations.

This viewpoint intends to create awareness about the use of IDP for unstructured documents, outlining the key differences between the application and benefits of IDP for unstructured documents versus semi-structured documents.

Scope

All industries and geographies

Contents

In this research, we study:

• Document processing challenges for enterprises
• Emerging IDP solutions with capabilities for unstructured documents
• The application of IDP for unstructured documents
• Key considerations and best practices to ensure successful IDP adoption, including an enterprise case study

Membership(s)

Service Optimization Technologies (SOT)

Sourcing and Vendor Management