Everything You Should Know About AI Document Analysis

Everything You Should Know About AI Document Analysis

According to a study conducted by McKinsey, a third of all tasks at the workplace are the ones that can most easily be automated with the right tech at hand, i.e. AI document analysis, processing, automation, and more. This, put together with intelligent document processing, or IDP (tools like KlearStack), can work wonders for efficiency and optimization at the workplace. This is what we mean when talking about document analysis and processing using AI.

Artificial Intelligence (AI) is such that it can be adapted to a number of programs. Because AI is constantly learning and changing its own algorithm using the machine learning (ML) process, it takes to any industry or program rather efficiently. According to a study conducted by Gartner, usage of AI in the workplace went up a whopping 270% in four years, between 2015 and 2019, where the most growth came in 2018-19. This only means that the world is becoming more and more inclined towards adopting AI tools like KlearStack at an increasingly rapid rate.

Some of the processes that can be enhanced in the workplace using artificial intelligence are as follows:

  • Business productivity
    • Invoice processing
    • Data entry
    • Data analysis
    • AI document analysis
    • Customer experience & analysis
    • Sales and business development
  • Data visualization & representation
  • Data testing
  • Natural Language Processing (NLP)

Essentially, an AI system can be built and adapted for any process as long as there is an idea in place on how to maximize efficiency with it. There are different systems and algorithms in place for each of the uses mentioned above, and different companies specialize in one or more of the same. In this blog, we will be focusing particularly on how one may use artificial intelligence to automate data and document analysis in the workplace.

What Does AI Document Analysis Mean?

Using artificial intelligence for document analysis makes use of natural language processing (NLP) and the machine learning process (ML). It functions in quite the same way a human would analyze a document, especially documents with numbers and figures. A survey from 2022 shows that 91% of all top businesses across the world have adopted AI in some form or another. AI document analysis is one of the more common programs adopted by companies because of its generalized nature.

No matter the field or industry you work in, IDP backed by AI can help maximize the efficiency of your workplace in several ways. Take a look at some of the examples below to understand better where AI-backed document analysis can be used:

  • Manufacturing companies can use it for processing order forms, change requests, and other documents.
  • Financial companies can use it for processing different service requests.
  • Healthcare facilities for patient onboarding, patient record management, etc.
  • Government & related agencies for processing surveys and other data.

The AI document analysis process: how does it work?

It’s noteworthy that one of the first few commercial uses of AI was to process documents. The aim of AI is and has always been to build technology that resembles true human action as much as possible. Extending this, it also serves the purpose of making life easier for the humans whose jobs mainly pertained to poring through documents, and to find ways to make this much less tedious.

AI document analysis works because it identifies and extracts structured as well as unstructured data from documents, then puts it into formats that are easier to compile and analyze. It uses the following components to make the final product:

  • Machine learning
  • Natural language processing
  • Neural networks & deep learning

Using machine learning, one can teach AI tech to recognize and compile this data in a particular way – it learns and understands user behavior over time. The role of natural language processing here is to allow the computer to identify, comprehend and interpret text (and even speech). Neural networks pertain to networks of information in your computers. It combines with deep learning by deep diving into your computer system to make and find relevant connections.

Here are the steps involved in document analysis using AI:

  • The document requiring analysis is input for the system to assess.
  • The AI identifies the kind of document it is and categorizes it as such.
  • The information is extracted using NLP.
  • The data is validated using ML, deep learning and the neural networks, it extracts what’s necessary and does away with the rest.
  • Straight-through processing (STP) ensues and enables you to view your data in the format of your choosing: as a sheet, document, etc.

It’s a fairly simple process that several companies across the world have very well mastered and offer you the service on rolling plans. It’s worthwhile to look into availing AI document analysis for your workplace, especially if you generally deal with large volumes of textual content.

Benefits of AI document analysis

The following are some of the top benefits of using AI particularly for analyzing documents.

  • It saves a lot of time

Comprehensive research tells us that using AI in the workplace saves approximately 30 to 40 per cent of the hours that it would generally take on tasks that can now be automated with this tech.

  • It reduces costs significantly

A research study carried out by McKinsey tells us that a whopping 44% of companies with integrated AI have reported less business costs, and 40% reported revenue growth of up to 5% after adopting any AI program.

  • It provides for much higher workplace productivity

A SnapLogic study from 2021 tells us that 81% of all interviewed workers believe that adopting AI in the workplace improves their own performance. More than anything else, this speaks to the value that AI brings to the workplace and the willingness of employees to adopt the same.

Ashutosh Saitwal
Ashutosh Saitwal

Ashutosh is the founder and director of the award winning KlearStack AI platform. You can catch him speaking at NASSCOM events around the world where he speaks and is an evangelist for RPA, AI, Machine Learning and Intelligent Document Processing.