AI and Machine Learning is making Document Processing Intelligent

October 04, 2024

The volume of unstructured data from documents such as contracts, invoices, and customer communications grow exponentially, as businesses increasingly adopt digital solutions. This data needs to be processed and stored in structured systems for easy retrieval and further analysis. Traditional document processing methods are some combination of manual and Optical Character Recognition (OCR) platforms. These are often inefficient, error-prone, and resource-heavy as OCR platforms still struggle with unstructured information sets.  

Intelligent Document Processing (IDP), powered by AI and Machine Learning (ML), is making the processing independent of the format or structure of the information set resulting into automation of the entire process, delivering greater accuracy and efficiency. 

The Growing Demand for IDP 

The global IDP market was valued at USD 1.75 billion in 2023 and is expected to reach USD 19.32 billion by 2032, growing at an impressive CAGR of 30.5%​. (Fortune Business Insights). This growth is driven by the need for businesses to process large volumes of data quickly and efficiently.  

Key Applications of AI in Document Processing: 

  1. Automated Data Extraction: AI systems proficiently extract pertinent data from various documents—ranging from invoices to forms—thereby curtailing the reliance on laborious manual data entry. This shift not only streamlines operations but also bolsters decision-making. 
  2. Document Classification: Utilizing AI, documents are seamlessly categorized into predefined groups, an essential function in sectors like legal, finance, and healthcare, which manage substantial document arrays. For instance, in trade finance, AI can efficiently sort documents such as bills of lading and certificates of origin. 
  3. Compliance and Risk Management: AI enhances compliance by detecting sensitive information within documents and automating critical processes such as redaction and data masking to safeguard personal data. 

We see accuracy, faster turnaround time, and compliance are critical— leading to the adoption of these technologies. 

AI and ML: The Backbone of IDP 

These days, when there’s a mention of accuracy, turnaround time, and efficiency, there must be an application of Al & ML. This self-learning technology is changing all industries and here’s how it is revolutionising IDP: 

  1. Contextual Understanding: AI-driven IDP systems can interpret data points based on the context within the document. For example, they can distinguish between several types of documents—like purchase orders and tax forms—and extract relevant data, accordingly, reducing the need for manual oversight. 
  2. Continuous Learning: Machine Learning algorithms allow IDP systems to learn from new document inputs over time. This capability improves accuracy and adaptability, enabling systems to process new document formats with minimal human intervention. 
  3. Enhanced Accuracy: Modern IDP platforms can achieve high accuracy with minimal training. For instance, Cogniquest (https://www.cogniquest.ai), our portfolio company, utilizes its native proprietary AI platform to process data/documents with high accuracy, offering automation for document-intensive industries such as banking, finance, and healthcare with minimal training data set. 

The Future Trajectory for IDP 

  1. Advanced AI Capabilities: Ongoing AI advancements are set to refine document processing tools further, enabling them to perform complex tasks autonomously, such as decision-making based on the document’s content. 
  2. Integration with SaaS Platforms: Future AI document processing tools will likely integrate seamlessly with popular Software as a Service (SaaS) platforms, enhancing usability and scalability. This integration will enable organizations, regardless of size, to leverage sophisticated document processing tools without substantial initial investment. 
  3. Expansion of Use Cases: With AI evolution, new applications for IDP will emerge across various sectors, including the contextual analysis of legal documents, tax return preparations, and even personalized marketing material creation. 

The future of intelligent document processing lies in leveraging AI to transform how organizations handle and utilize content within the documents. By embracing these technologies, businesses can achieve greater efficiency, accuracy, and cost savings, positioning themselves for success in the digital era. 
 

Conclusion 

AI and ML are driving the next wave of innovation in Intelligent Document Processing, transforming how businesses manage and utilize their data. Platforms like Cogniquest are at the forefront and enterprises can automate complex processes, reduce costs, fasten training and prepare for the future of work. In this rapidly evolving landscape, adopting IDP solutions has transitioned from a luxury to an essential strategy for organizational efficiency and scalability.

Jeet Vasa
Jeet Vasa