With digital transformation (DT), companies are integrating new tools and processes that allow them to improve how they work. Data conversion companies support the ongoing digital transformation by helping organizations process information from their countless documents. Manually processing information from documents, including digital files such as PDFs, images, spreadsheets and video, is costly and prone to errors. Artificial intelligence (AI) has transformed business document processing as it has the ability to extract from structured and semi-structured data with high levels of accuracy.
Role of AI in Business Document Processing
Modern organizations store data in multiple sources, including customer relationship management (CRM) data, financial data, spreadsheets, PDFs, documents, files, images, etc. Data extraction involves collecting and consolidating the information from these sources so that it can be stored in the required formats for further use.
Robotic process automation (RPA) automates document processing workflows and enables highly repetitive and high-volume processes to be done faster and more accurately. However, RPA alone is insufficient since all that data in business documents need to be read and entered correctly into record systems. Manually processing information from large volumes of documents is a costly and error-prone process.
This is where AI-led document processing comes in. It overcomes the challenges of extracting data accurately from large volumes of documents.
How AI-powered Document Processing Works
AI-powered intelligent document processing (IDP) solutions can effortlessly and accurately extract and process data from multiple documents in different formats. IDP-powered solutions use a blend of AI technologies to classify, categorize, and extract relevant information from unstructured and semi-structured documents and images and validate it:
- Natural Language Processing (NLP): A subset of AI, NLP can process and comprehend documents. IBM defines NLP as the ability of a computer program to understand human language as it is spoken and written (IBM). It uses syntax and semantic analysis to understand the grammatical structure of a text and identify how words relate to each other in a given context. NLP supports multiple languages and is ideal to analyze large volumes of text data such as social media comments, online reviews, news reports, and more.
- Computer Vision: Computer vision makes it possible to understand and extract meaning from digital images. While Optical Character Recognition (OCR) focuses on recognizing text, computer vision analyzes different document layouts from scanned images, PDF files, and digital and paper-based files. Computer vision can recognize and extract meaning from non-textual elements like tables or graphs.
- Deep Learning and machine learning (ML): Machine learning a subfield of AI that focuses on using data and algorithms to imitate the way that humans learn, and improve its accuracy. Deep learning absorbs unstructured data in text, image and other formats and automatically determines the features that differentiate various categories of data from one another. As deep learning models are trained using a large set of labeled data and neural network architectures, they provide very high levels of accuracy.
- Fuzzy Logic: Fuzzy Logic (FL) is an approach of reasoning that mimics human reasoning. While it is similar to the human decision making process, this method is much faster. Fuzzy logic improves efficiency across systems and business processes by supporting decision making.
By making data extraction seamless and highly accurate, AI has not only redefined but reinvented how organizations use digital documents, notes a Forbes article.
| Read More:
Future of Robotic Process Automation (RPA) What is Intelligent Document Processing? Top Benefits of Using Intelligent Document Processing |
Advantages of AI-powered Business Document Processing
- Converts both unstructured and semi-structured data into structured, usable information, enabling end-to-end automation of document-centric business processes
- IDP tools can be easily integrated across an enterprise and are widely applicable across industries and business functions
- Supports greater flexibility and scalability in document processing with minimal manual intervention
- Propels faster automation of document-centric processes and improves overall business efficiency
- Reduces expenses by allowing processing of large volumes of data in a cost-effective manner
- Minimizes the need to hire knowledge workers to process documents
- By minimizing repetitive, low-value tasks, AI-powered document processing reduces associated overhead costs
- Automated data entry services improve speed and accuracy
- Sales, marketing and customer departments can leverage data generated by AI-powered models to predict customer behavior, improve response times, and enhance their buying experience
Business process outsourcing services are helping both large and small businesses take advantage of AI-powered solutions. Data conversion outsourcing to an experienced service provider can help businesses transform their document management processes and improve overall workflow, efficiency and revenue.
