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November 02, 2023

AI Document Processing: What is the Use of AI in Document Processing?


Artur Haponik

CEO & Co-Founder

Reading time:

10 minutes

95% of corporate information exists in the form of paper documents. [1] As such, organizations require a tremendous amount of time and effort to file, retrieve, and reproduce lost documents, causing inefficiencies within the organization. While some organizations have adopted the use of Optical Character Recognition (OCR) in a bid to go digital, these systems do little to ease the document processing burden for organizations. However, when combined with AI document processing technologies, the possibilities for seamless document processing within organizations become limitless.

This article will evaluate the intricacies of AI document processing, evaluating everything from the technologies employed, to how they could benefit your organization and the future of intelligent document processing.

AI in document processing: A quick look

The advent of intelligent document processing with artificial intelligence, machine learning and associated technologies started with the development of OCR. [2] Traditionally, organizations had to file, sort, and analyze documents manually. The advent of OCR revolutionized document processing by enabling organizations to scan and store documents in digital formats, which could be easily stored, sorted, and reviewed from a central database.

Fast forward a few decades, and AI came into play. AI gave rise to intelligent document processing (IDP), which applies AI and ML techniques to capture, extract, and process data from various types of document formats. Over the years, the technology has evolved to incorporate other intelligent capabilities like natural language processing to facilitate seamless document analysis.

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AI for document processing leverages artificial intelligence, machine learning, and other associated technologies to automate data processing processes. The system also takes things up a notch by ‘reading and understanding’ text data, enabling organizations to extract relevant information quickly and accurately.

In order to achieve this, document processing using AI follows four distinct steps, namely:

How AI-based document processing works


AI for document processing doesn’t work with physical documents. Therefore, organizations have to digitize physical documents with OCR systems before they can be fed into the system. Besides scanning physical documents with OCRs, organizations can also import digital documents through uploads, email transfers, or secure file transfers.


Once the documents are imported into the IDP system, the software seeks to understand the document layout through AI, ML, and natural language processing technologies to classify them. For instance, the system can classify imported documents as medical forms, customer feedback forms, or invoices. Once the system understands the nature of the document, it can start to figure out how to read the document.


At the extraction stage, the AI document processing system pulls data from the document and transforms it into usable form. The extraction process is fully dependent on the data format of the documents in question.

Data from ingested documents typically comes in three formats: structured, semi-structured, and unstructured data. Structured data is generally well-defined, with clear outlines and labeled database fields, making it easy for the software to use.

Conversely, unstructured data mainly presents itself as a string of numbers or letters with undefined parameters, making it nearly impossible for artificial intelligence systems to read. Semi-structured data is an aggregated mixture of the two and, therefore, requires further processing to turn it into a machine-readable format. [3]

Therefore, the primary goal of the extraction stage is to extract information from structured data and convert unstructured and semi-structured data into machine-readable formats that the AI-based document processing software can work with.


Artificial intelligence and machine learning systems learn over time, but that doesn’t mean that the intelligent document processing system is entirely hands-free. At best, the system takes a well-educated guess on the nature of the document and the type of information that it should extract. The verification responsibility falls on the hands of human employees who check whether the system is correct.

However, when the system is leveraged correctly by combining AI capabilities with machine learning, the AI document processing system learns from the humans’ feedback and improves over time. Eventually, the system makes more accurate verifications, thus reducing the amount of human intervention needed to verify documents.

Read more about How AI is revolutionizing document analysis: A comprehensive guide

Advantages of AI document processing

Artificial intelligence and machine learning has completely revolutionized document processing. With AI document processing, organizations can automatically sort through documents, retrieve necessary information, and ultimately eliminate the bottlenecks of traditional document processing.

Here are a few ways in which AI-based document processing could benefit your organization:

Mitigate data inaccuracy

Traditional, manual data entry, storage, and verification are prone to human error, resulting in multiple inaccuracies that could lead to problems such as inaccurate insights, poor business intelligence in decision-making, and potential compliance issues.

AI document processing limits and, in some cases, eliminates the need for human intervention, especially when it comes to data entry, thus reducing the possibility of error. AI document processing systems can effectively identify, extract, and validate text data through AI-based technologies like deep learning, machine learning, and NLP to ensure high levels of accuracy in document management.

Handle high volumes of data

The volume of data any organization possesses grows in tandem with the organization. This means that as your business grows, so does the data it has to handle, process, and store. With time, traditional document processing methods become unreliable due to increased delays, which, in turn, lead to missed deadlines and customer dissatisfaction.

AI-based document analysis can handle an incredibly large volume of data. What’s more impressive is it scales along with your organization, enabling you to maintain high efficiency levels even as your organization grows. This ensures timely and accurate AI document processing at every stage of the organizational growth process.

AI-based document categorization

One of the biggest benefits of AI document analysis is its ability to leverage artificial intelligence, machine learning, and other associated technologies to categorize documents into various datasets based on their content.

AI-based document categorization

For instance, an intelligent document processing system can be trained to identify specific documents, such as legal documents, invoices, or contracts, and automatically route them to the relevant department within an organization. This effectively reduces human errors associated with manual document categorization and helps streamline workflows.

AI-based document automation

Even the most robust document management system has a few bottlenecks when it comes to document recovery, particularly when it comes to large databases with similar documents. Intelligent document processing systems have automation capabilities that leverage natural language processing to generate custom responses based on templates or documents automatically.

AI-based document automation

This eliminates the need to spend countless hours sorting through documents when creating contracts or responding to customer queries since the system can generate relevant responses in seconds.

Improved customer service

Most customer service emails go unanswered, with a small majority of customers getting a response after 12 hours. This is despite the fact that most customers expect a reply within one to four hours. [4] The result is often customer dissatisfaction, which could cause them to go to your competitor, causing you to lose business.

Intelligent document processing doesn’t just work on text documents. The system can also be configured to retrieve and process complaints through NLP-powered chatbots. Alternatively, organizations can train the system to prioritize and forward urgent and important emails to customer service staff, leading to faster, more streamlined customer service.

The same notion applies to companies that rely on huge stacks of documents to process customer service processes. Take hospitals, for instance. For decades, hospitals have relied on physical documents to store patient records. Despite employing an elaborate document management system through filing, finding patient documents can be quite a hustle, especially if they’re misplaced or mislabeled.

With AI-based document processing, hospitals can effectively store and retrieve patient records in seconds, thus reducing the time and effort it takes to retrieve documents and facilitating faster service delivery.

Increased productivity

Document processing is a painstaking, time-consuming process that significantly impacts productivity. Traditional document processing methods typically involve manually searching for individual documents for every request, which can be quite counterproductive for large organizations dealing with a huge volume of documents.

With AI-based document processing, organizational staff can easily access stored documents and retrieve important information instantly. This significantly reduces the time and effort it takes to retrieve documents, thus freeing up the employees’ time and enabling them to focus on more important duties. The result is a significant boost in productivity that could significantly improve an organization’s income and market competitiveness.

Discover more about AI-driven text summarization: Challenges and opportunities

Upcoming trends in AI document management

AI-based document processing might seem pretty modern, but that’s just the start of it. As tech companies and startups continue to innovate, the technology will only get better with time. In fact, looking at current AI-based document processing dynamics, it’s clear that there are already trends paving the way for more streamlined and effective document management practices that will pave the way for the future of intelligent document processing.

Here are some of the most notable upcoming trends in AI document management:

Cloud storage and intelligent document automation

More than 60% of corporate data is stored in the cloud. [5] The driving factor behind most businesses choosing the cloud as a preferred storage solution is the level of security and ease of access the technology provides. Cloud storage solutions are heavily encrypted, making them one of the most secure solutions for document storage. Additionally, stored documents can be accessed from anywhere in the world, as long as there’s an internet connection.

Besides security and ease of access, cloud storage solutions offer various other beneficial features, including version control and automated backups, making it easy to manage and collaborate on documents.

Cloud storage also offers tremendous potential for scalability, enabling businesses to easily expand their storage capacity as their business needs grow. As more businesses move towards robotic process automation and remote work, cloud storage will increasingly become a vital tool to ensure efficient and secure document management practices.

Increased use of RPA and BI technologies

Robotic Process Automation (RPA) can automate repetitive, time-consuming tasks such as data entry, verification, and extraction, freeing up employees’ time and energy to focus on more critical tasks. Similarly, Business Intelligence (BI) technologies can provide valuable insights into document management practices, such as optimizing workflows and identifying bottlenecks in document management.

By combining these technologies, organizations can reduce processing time, automate document management workflows, and gain helpful insights into their document management processes, thus improving efficiency and productivity.

As robotic process automation and business intelligence technologies evolve and become easily accessible, more businesses will continue to adopt the technologies, leading to a major shift in document management practices.

Mobile-friendly deployment

As mobile devices continue to infiltrate the market, organizations and businesses will need to ensure that their document management and processing systems are accessible on mobile devices. This way, businesses can better provide their staff with the ability to share, access, and collaborate on documents from any device.

Mobile-friendly deployment can also significantly improve user experience, making it easier for employees to access and navigate document management systems, which will ultimately lead to increased productivity and user satisfaction.

Final thoughts on document processing with AI

The development of OCR and the subsequent digitization of documents paved the way for businesses to utilize AI-based technologies like intelligent document management to streamline workflows and improve productivity. As AI-based document processing technologies continue to evolve and become more accessible, we will see more organizations adopting the system, thus leading to a complete overhaul of traditional document management practices.


[1], Document Management Facts and Figures,, Accessed on October 25, 2023
[2], The Evolution of Intelligent Document Processing, , Accessed on October 25, 2023
[3], What’s the Difference Between Structured, Semi-structured, and Unstructured Data?, Accessed on October 25, 2023
[4], Customer Service Benchmark Report,, Accessed on October 25, 2023
[5], Navigating Data Security in an Era of Hybrid Work, Ransomware and Accelerated Cloud Transformation, Accessed on October 25, 2023


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