Close this search box.

Document Processing Puzzle Finally Decoded with AI

Intelligent Document Processing

According to a Gartner news release, finance departments can save 25,000 hours of rework due to human errors at the cost of $878,000 per year for an enterprise with 40 full-time accounting personnel by implementing intelligent document processing systems.

Isn’t that surprisingly huge?

Intelligent document processing improves human understanding of unstructured data through data science methods, including computer vision, optical character recognition, machine learning, and natural language processing.

Intelligent document processing is slowly gaining traction because it offers solutions for automating data extraction processes that were cumbersome and confusing, if not impossible, to complete.

The single platform solution is what’s new, and it’s changing the way we work. New data sources improve corporate outcomes and open the road for human-driven innovation.

Intelligent document processing solutions are sophisticated software that feeds tagged data into the data supply chain from any text-based source.

Let’s first understand intelligent document processing and how it works?

The extraction and processing of data from various documents using intelligent document processing is nothing but the RPA magic at play. It automates document processing with deep learning technologies. Intelligent document processing collects unstructured data from documents (e.g., email text, PDF, and scanned documents) and converts it to structured data using RPA bots, AI, and computer vision. 

“Intelligent document processing,” as defined by Deloitte, “automates the processing of data included in documents by recognizing what the document is about, what information it contains, extracting that information, and transferring it to the appropriate location.”

AI-led automation solutions are ready to eliminate the information gap between people, documents, and machines by combining deep learning’s neural networks with the scalable processing capacity of the cloud. 

This new capability has got the potential to provide four critical benefits to employees and businesses:

  1. Acceleration of digital transition

Many businesses are struggling to progress in their digital transformation efforts, with an estimated $900 billion wasted investment in 2018. Inadequate access to operational data, much of which is held in papers, is a major roadblock to long-term reform. By automating document processing, businesses can reduce costs and provide a rich data source for automated workflows and systems. The data gathered regarding how the documents are handled, as well as the information contained in these freshly processed documents, can provide valuable insights for further process refinement and operational performance improvements.

2. Driving a more rapid return on investment

In days or weeks, AI-driven automation document processing systems can be set up, configured, and trained (rather than months or years). Document modeling without code saves time that would otherwise be spent designing hundreds of document templates, granular programmed rules, and information locators. Enterprises may use automated document processing for a wide range of documents with a cheaper total cost of ownership, achieving ROI faster than traditional technologies.

3. Improved operational responsiveness and openness in terms of compliance

Most AI document processing services were previously only available as API services that took documents and returned results in a text file. AI-powered automation can now offer “human-in-the-loop” validation, in which the individual submitting the document receives the classification and extraction results. This allows for near-real-time information verification and correction. While interacting with customers, partners, or other external stakeholders, front-line workers can swiftly make mistakes or request additional information. This saves time while also improving data accuracy and transparency for all parties engaged in a business process.

4. Enhanced operational adaptability

Deep learning AI allows for rapid document modeling and training, allowing for the swift addition of new, never-processed documents to the document processing system. Furthermore, with shorter lead times, businesses may respond rapidly to new opportunities by developing new document processing apps without having to hire more people. Non-specialized workers can quickly train and operate the system thanks to no-code modeling, which reduces the need for highly qualified technical personnel.

The time for intelligent document processing is finally here, creating a new technology-driven era. True, the moment is right for intelligent document processing, with AI playing a key role in document processing advancement. There will be more innovation in this field in the future.

• First, AI models will need to stay up as the forms and structures of semi-structured and unstructured documents continue to evolve. AI models will be tested in a variety of ways, from reading overly complex table structures to processing government-issued IDs with holograms or watermarks.

And this is exactly where AutomationEdge has been a pro, helping an organization with the gigantic task of Aadhar masking!

• Second, while intelligent document processing has been coined for this domain, video, and audio file types are on the rise. It’ll only be a matter of time until these file types are used to process insurance claims or file tax returns.

Hands typing on a laptop with futuristic holographic AI in IT interface graphics symbolizing artificial intelligence technology in information technology.
No-code low-code AI Platforms

Explore our topics