Intelligent Document Processing Market Overview:
TheIntelligent Document Processing market growth industry is projected to grow from USD 1,465.6 million in 2022 to USD 14,789.7 million by 2030, exhibiting a compound annual growth rate (CAGR) of 33.5% during the forecast period (2022 - 2030). The increasing need for businesses to handle large volumes of semi-structured as well as unstructured documents with higher accuracy and speed, growing investments within digital transformation, as well as the increased adoption of cloud-based document processing remedies are among the leading driving factors in the Intelligent Document Processing market's development.
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Key Players:
Key Companies in the Intelligent Document Processing market include,
- IBM (United States)
- Kofax (United States)
- WorkFusion (United States)
- ABBYY (United States)
- Automation Anywhere (United States)
- Appian (United States)
- UiPath (United States)
- Datamatics (India)
- Deloitte (United Kingdom)
- AntWorks (Singapore)
Market Segmentation:
Component, organization size, technology, deployment model, and vertical have all been divided in the worldwide intelligent document processing market.
The intelligent document processing industry has been divided into solutions and services depending on the component. The solutions segment held the most market share and is predicted to continue to do so over the forecast period. This is due to the widespread usage of powerful intelligent processing software solutions across industries. On-premises and cloud-based solutions are being deployed.
The intelligent document processing industry is divided into on-premises plus cloud-based deployment modes. During the projection period, the cloud-based deployment paradigm is predicted to rise at a substantial CAGR. The software as a service concept has exploded in popularity among small and large organizations in recent years. A hybrid cloud method is being used by several large organizations to implement cloud-based models.
Natural Language Processing (NLP), Robotic Process Automation (RPA), Optical Character Recognition (OCR), Google Vision, Machine Learning (ML), Deep Learning (DL), and Artificial Intelligence have been classed as segments of the intelligent document processing industry dependant on technology (AI).
The global intelligent document processing industry is divided into two categories: small and medium-sized businesses and large businesses. Within the market, the small and medium-sized enterprises category held the largest market share.
The intelligent document processing industry is fragmented into BFSI, retail and e-commerce, government and public sector, manufacturing, transportation & logistics, healthcare, and life sciences, and many others, depending on verticals.
Regional Classification:
During the forecast period, the global intelligent document processing industry is estimated to generate considerable revenue from various continents. For the Middle East and Africa, North America, Asia-Pacific, Europe, and South America, a geographical analysis of the worldwide intelligent document processing industry was undertaken.
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Industry News:
According to different estimates, 80 percent of enterprise data is unstructured, hence traditional automation solutions struggle to automate processes using unstructured data. When a company expands, so do the procedures, the number of clients, and, eventually, the volume of incoming documents. To stay competitive, businesses are dealing with bigger volumes of semi-structured and unstructured information that must be processed faster and more correctly than before. Manually processing these massive volumes of papers takes an inordinate amount of time. As a result, businesses are increasingly required to analyze massive amounts of semi-structured and unstructured documents more accurately and quickly.
The practice of intelligently acquiring specific information and expediting document processing processes is known as intelligent data processing, sometimes referred to as intelligent data capture. Intelligent document processing is meant to perform document scanning activities regardless of the type of file that has to be processed. Data capture makes data management simple for any company. The information can be organized more quickly and efficiently now that the documents have been converted to digital format.
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