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The Future Of AI-Powered Document Processing

The Future Of AI-Powered Document Processing

In today’s digital world, documents remain essential to the way we exchange, communicate, understand and store information and ideas. Where IT systems are concerned, however, documents are somewhat problematic.

Machines are good at processing structured information that can be stored and queried in things like relational databases, CRM systems and ERP programs. Documents do not fit neatly into those structured architectures. Yet, for human-to-human interactions, documents remain indispensable.

The human mind simply does not compute things like machines do. We need to visualize information and ideas to readily comprehend them. Graphs, tables, text, engineering drawings, etc. are human-centered expressions of thought and information. Documents are the carriers of vital information and ideas that humans need to make decisions.

Thus far, in the long history of documents, humans have been indispensable to the processing of documents—consuming the content, extracting information, understanding what’s in the document and making decisions accordingly. Only humans have been able to complete the process from end to end.

This limitation is fading, however, with the continued evolution of artificial intelligence. In the near future, machines will likely be able to process documents from end to end without major human intervention. AI-powered systems will be able to readily understand documents, extract information and thoughts and make decisions based on the content.

That transformation is already significantly underway. As we have all read, generative AI platforms like ChatGPT, which utilize natural language processing and large language model algorithms for deep learning, can recognize, summarize, translate and create content with increasing accuracy when properly trained.

PDF And AI Are Leading Intelligent Data Processing

PDF software, a universal document technology, is being extended by generative AI to increasingly take over work that once could only be performed by humans. PDF functions like redaction to protect private and sensitive information are now being automated through the use of generative AI to achieve major improvements in efficiency and work quality.

AI is expanding the power of simple optical character recognition to recognize and extract relationships, structure, text, graphs and other characteristics of documents to deliver new capabilities like summarizing, editing and creating documents within the PDF format.

The opportunity is there for AI to automate entire document processes—call it “intelligent document processing.” In banking, for example, loan officers review applications and supporting documents and then make decisions about whether or not to grant a loan. In engineering and architecture, professionals create and review drawings and floor plans that must meet certain standards. AI may eventually automate those processes, with humans only required to oversee exceptions outside certain norms.

PDF is sometimes thought of as a static format for sharing and archiving documents that can’t be modified. However, the evolution of PDF over time has made the format extremely well-suited for all kinds of workflows before a file is archived. Interactive features, such as fillable forms, allow users to dynamically change data fields in PDF documents. The format has become a programmable platform with the introduction of JavaScript, enabling the customization of all types of user interactions. The introduction of 3-D objects, which can interact with other parts of a PDF document, have made it the de-facto format for 3-D engineering document exchange.

Today, PDF encompasses both structured and unstructured data. Metadata tagging of PDF documents enables the identification of lists, tables, headings and other elements, as well as the content itself, to make PDFs more accessible and useful in document workflows. Intelligent document processing, powered by generative AI, will make PDF exponentially more useful in workflows. PDF has unique advantages, such as environment independence, security, trackability and verifiability, that can position the format as a valuable data hub between systems.

Making Intelligent Document Processing A Reality

Making intelligent document processing possible requires two critical components. One is the intelligence optimized to analyze documents. The other is the domain knowledge to train and put that intelligence to work to deliver meaningful workflows such as loan approvals or the processing of engineering drawings or medical documents.

The document is a human-centric medium that will always be essential to the way we create, exchange, understand, preserve and take action on information and ideas. Making it more accessible to machine-based automation, however, poses significant challenges. AI-powered intelligent document processing holds the key to major breakthroughs in bridging the gap between the way humans and IT systems process information.

Intelligent document processing is not an out-of-the-box generative AI solution. AI platforms like ChatGPT are trained on huge volumes of publicly available data and not for specific domains and industries. Significant fine-tuning and training are needed to integrate with various document processes. Beyond that, it will need to be further trained by solution providers and businesses to understand and address specific vertical industry, company and individual workflows. This is currently an evolving process that requires human intervention, not just for training, but also for monitoring and measuring results.

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