Digital transformation enables companies to upgrade their methods through the use of new tools. Data conversion firms facilitate this process by offering organizations assistance in managing data from countless documents – digital files including PDFs, images, spreadsheets and video. Without AI, manually processing this information would be costly and inefficient; but thankfully AI has revolutionized business document processing with its expertise in extracting structured and semi-structured data with utmost accuracy.
Role of AI in Business Document Processing
According to Jimmie Hamilton, CEO & Founder of Hi Home Picks, there are many sources of data in modern organizations, including customer relationship management (CRM) data, financial data, spreadsheets, PDFs, documents, files, images, and others. In order to store the information in the required formats, the information from these sources must be collected and consolidated.
Automating document processing workflows with robotic process automation (RPA) allows highly repetitive and high-volume processes to be executed more efficiently and accurately. RPA alone is not sufficient since all that data in business documents needs to be read and entered correctly into record systems. The process of manually processing large amounts of documents is costly and error-prone.
Artificial intelligence-led document processing overcomes the challenges of extracting data accurately from large volumes of documents.
How AI-powered Document Processing Works
Intelligent document processing (IDP) solutions powered by artificial intelligence can extract and process data from a wide range of documents in different formats in an effortless and accurate manner. By using AI technologies, intelligent document processing (IDP)-powered solutions classify, categorize, and extract relevant information from unstructured and semi-structured documents and images.
Natural Language Processing (NLP): It is a type of Artificial Intelligence that has the power to analyze and comprehend written or spoken documents. IBM defines it as a computer program with the skill to interpret human language, both in its spoken and written form (IBM). It leverages syntax and semantic analysis to understand sentence structure and how words associate to one another within a certain context. NLP can work with multiple languages which makes it perfect for examining vast amounts of text content like social media comments, online reviews, news articles, etc.
Computer Vision: Understanding and extracting meaning from digital images is possible with computer vision. Unlike Optical Character Recognition (OCR), computer vision analyzes document layouts from scanned images, PDF files, and digital and paper-based documents. Non-textual elements, such as tables and graphs, can be recognized and extracted meaning using computer vision.
Deep Learning and Machine Learning (ML): Are subfields of artificial intelligence that focus on leveraging data and algorithms to replicate how humans learn, while achieving a high level of accuracy. Deep learning utilizes unstructured data such as text, images and other formats to determine the features that distinguish different types of data from each other. Furthermore, with its large datasets and neural network architectures, deep learning models are capable of providing significantly higher levels of precision than conventional machine learning techniques.
A fuzzy logic approach mimics human reasoning, but is much faster than a human decision maker. Fuzzy logic improves efficiency across business processes and systems by supporting decision-making.
AI has revolutionized the way organizations use digital documents by making data extraction seamless and highly accurate.
Advantages of AI-powered Business Document Processing
During our interview with Vaibhav Kakkar, the CEO & Founder of Digital Web Solutions, he discussed the significant benefits of utilizing AI-powered technology for business document processing.
- Enables end-to-end automation of document-centric business processes by converting both unstructured and semi-structured data into structured, usable information.
- A wide variety of industries and business functions can benefit from the use of IDP tools within an enterprise.
- Provides greater flexibility and scalability in document processing with minimal manual intervention.
- Improves overall business efficiency by automating document-centric processes.
- Allows for cost-effective processing of large volumes of data.
- Reduces the need to hire knowledge workers.
- AI-powered document processing reduces overhead costs by eliminating repetitive, low-value tasks.
- Speed and accuracy are improved by automated data entry services.
By leveraging AI-powered models, sales, marketing, and customer service departments can predict customer behavior, improve response times, and enhance the buying experience.
Both large and small businesses can benefit from AI-powered solutions thanks to business process outsourcing services. In order to improve workflow, efficiency, and revenue, businesses can transform their document management processes by outsourcing data conversion to an experienced service provider.