Drowning in paperwork? Whether it’s insurance, finance, healthcare, or manufacturing, documents rule all industries, from insurance claims and loan statements to patient signoffs. To deal with them, organizations enter digitization. According to Forrester, 65% deem integrating document digitization with daily apps crucial to keep their work flowing.

Automated document processing is a shortcut to ditching paperwork chaos and replacing it with document management efficiency, unleashing tech to manage, organize, and revolutionize documents effortlessly. To help you revolutionize document management, we are breaking down what it is, the tech behind it, and the game-changing benefits. Let’s dive in!

What’s Automated Document Processing?

Let’s start by explaining what document automated processing & understanding means. In essence, automated document processing is just what it sounds like—a set of technologies used together to streamline the handling and conversion of unstructured documents into structured formats. Each tool automates extracting, interpreting, or manipulating information from digital or scanned paper documents, images, PDFs, emails, or other documents.

Structured and unstructured data

Through AI and automation techniques, automated document processing systems can recognize and categorize data, extract relevant information, and perform predefined document-based tasks, eliminating manual effort.

Automated Document Processing and Intelligent Document Processing: What’s the Difference?

Intelligent document processing is an essential component of automated document processing. Both concepts are closely related and usually used together, due to which (and similarity in naming) they are often confused. Still, they aren’t the same.

Automated document processing focuses on automating rule-based document processing tasks using technologies such as Optical Character Recognition (OCR) and software automation. These tasks include data extraction or sorting.

While automated document processing can be efficient for specific tasks, it might require additional manual adjustments when applied independently to process unstructured documents or changes in document formats.

Intelligent document processing goes beyond basic automation by leveraging AI technologies such as machine learning (ML) and natural language processing (NLP) to enable systems to interpret, categorize, and validate the extracted data. Doing so enables intelligent document processing to adapt to variations and better handle unstructured documents.

Since automated document processing and intelligent document processing complement one another, automated document processing vendors often use these terms interchangeably.

Automated document processing vs. intelligent document processing

Automated document processing

Automated Document Processing (ADP) involves using technology to streamline routine document-related tasks, typically relying on rule-based systems. It focuses on efficiently processing information in documents; hence, its main applications include automating data entry and improving document classification.

Intelligent document processing

Intelligent Document Processing (IDP) employs advanced technologies like artificial intelligence and machine learning to automate tasks and understand and interpret unstructured data. It goes beyond automated document processing, offering a more nuanced understanding of content, and making it especially adept at handling diverse and complex documents in finance, healthcare, and legal industries.

Technologies Used in Automated Document Processing and Understanding

To properly extract, interpret, and classify documents, automated document processing makes use of several technologies:

Robotic Process Automation (RPA)

Robotic Process Automation refers to handing over repetitive, manual tasks to rule-based algorithms (bots) that can perform them faster and with a lower margin of error than humans. When it comes to automated document processing, this simple but efficient solution is often combined with AI in tools such as UiPath Document Processing, AA Document Automation, and IBM Document Processing. This pairing allows us to apply all of AI’s document understanding capabilities at scale and without human involvement.

Optical Character Recognition (OCR)

Optical Character Recognition identifies letters, numbers, and other characters in documents and images, which are then converted into accountable formats. This enables further automated data processing. OCR has as many applications as there are documents to extract data from invoices, orders, statements, recipes, etc.

Machine Learning (ML)

The use of AI algorithms, statistical models, and data to imitate the way humans learn. With Machine Learning, AI doesn’t require explicit instructions. Instead, it can “study” data to gradually improve at specific tasks. ML allows AI to improve its accuracy with each document handled continuously in document processing. With that, outputs provided by artificial intelligence require less verification, giving humans more time to focus on other tasks.

Natural Language Processing (NLP)

Natural Language Processing aims to allow computers to interpret and generate human language through text or voice outputs. To achieve that “understanding,” NLP combines rule-based and statistical modeling with machine learning. NLP is a cornerstone of any language-centered application, like chatbots, virtual assistants, speech-to-text software, translation tools, and more.

Generative AI

With the release of Gen AI tools like Chat GPT or Midjourney, generative AI has been in constant spotlight due to its creative content-generation capabilities, previously unseen in machines. Gen AI finds a perfect application in automated document processing, where it’s used to humanize ADP tools through natural language prompts and produce content like document summaries or complex answers to user requests.

Cognitive computing

If natural language processing aims to mimic human linguistic capabilities, cognitive computing tries to reproduce our problem-solving and complex thinking processes. These skills are fundamental when processing unstructured data, exceptions, or deviations from patterns.

The Benefits of Automated Document Processing

Now, the part you’re probably the most interested in: what can you gain by implementing automated document processing?

What to improve with automated document processing

Automated Document Processing Across Industries

Any company can reap the benefits of automated document processing from increased efficiency to faster decision-making, no matter the industry. However, documentation, data, and tasks vary depending on the sector. Here are some industry-specific applications of automated document processing.


The healthcare industry already relies largely on digital data formats. In the US, 78% of office-based physicians and 96% of non-federal hospitals use a certified EHR system. Automated document processing software is crucial for converting and organizing all medical records.

  • Patient record management: Automated document processing allows healthcare professionals to access critical patient data faster.
  • Clinical trial documentation: Between approvals, reports, reviews, and other documents, clinical trials involve lots of paperwork that laboratories can expedite through automated document processing.
  • Claims processing: With automated document processing, clinics and practitioners can accelerate reimbursement and handle insurance claims and medical bills without errors.

Finance & Banking

Finances Online says knowledge workers lose 50% of their time preparing documentation. Automated document processing is the perfect answer to these inefficiencies, helping banks reduce manual document-focused tasks.

  • Loan processing: Through automated document processing, the verification of financial documents becomes much faster, expediting loan approval processes.
  • KYC processes: Automated document processing streamlines the extraction and verification of customer credentials and helps banks meet regulatory requirements.
  • Invoice processing: Automation improves the speed and accuracy of financial statement and invoice processing workflows.


On average, insurers handle over 100,000 documents annually, 80% of which is unstructured data. This creates ample opportunity for automated document processing in insurance to take over mundane paperwork.

  • Policy administration: Managing insurance policies, processing policy applications, and extracting relevant data for underwriting can all be expedited through automated document processing.
  • Policy renewals: Automated document processing ensures that policy renewal documents are processed timely and that coverage is kept current.
  • Claims adjudication: With automated document processing, insurers can speed up the evaluation of claims documents and the entire claims review cycle.


Manufacturing involves tons of documentation flowing internally and between each link of the production chain. The communication is still largely unautomated, with over 40% of manufacturing orders being placed through fax or email and manually entered, according to Digital Commerce 360.

  • Supply chain management: Automated document processing helps companies efficiently manage sales orders, shipping documents, invoices, and customs paperwork, resulting in streamlined supply chain operations.
  • Quality control: By automating the handling of product control documents, manufacturers can ensure strict adherence to quality procedures.
  • Product manuals and compliance: Manufacturers can apply automated document processing to manuals, specifications, and compliance certificates to warrant that their products are accessible and follow industry standards.

Real estate

64% of companies surveyed by Deloitte see many use cases for AI in real estate. One of the potential applications is relieving agents of mundane paperwork tasks.

  • Contract management: Data contained in contracts, lease agreements, invoices, and other transaction documents can be extracted and added to your management system automatically.
  • Mortgage Processing: Automated document processing streamlines the processing of mortgage documents, such as applications, appraisals, and title deeds, for faster mortgage approval and disbursement.
  • Property valuation: Automated document processing can quickly extract property-related data needed in the property valuation process.

Automated Document Processing: Where to Start?

Automated document processing has the undeniable potential to revolutionize documentation-focused workflows in your business. However, to get to that point, you must consider various factors.

automated document processing system in 7 steps

Automated Document Processing with Flobotics

Now that you know what automated document processing is, how it works, and what it can do for your business, there’s only one thing to do: build your document automation system.

At Flobotics, we can guide you through the entire process. From assessment and deciding what process to automate to implementation and testing, our experts will help you replace manual documentation tasks with efficient, automated workflows. Let’s get started!

Like the article? Spread the word

Karl Mielnicki CTO of Flobotics

Karl Mielnicki

CTO & Co-Founder of Flobotics. Expert and fanatic in RPA - Robotic Process Automation with over 5 years of IT experience working for consulting companies and tech startups. UiPath consultant, an accredited BluePrism developer.

Process Automation
ROI Calculator

Considering automating your process? See what Return on Investment you can count on!