In today’s digital world, documents play a vital role in how we exchange, communicate, and store information. However, when it comes to IT systems, documents can pose challenges due to their unstructured nature. While machines excel at processing structured information, documents don’t neatly fit into those architectures. Despite this, documents remain indispensable for human-to-human interactions, as they carry vital information and ideas that humans need to make decisions.
The limitations of human involvement in document processing are beginning to fade with the continued development of artificial intelligence (AI). In the near future, machines may be able to process documents from start to finish without significant human intervention. AI-powered systems hold the potential to understand documents, extract information, and make decisions based on their content.
PDF software, a universal document technology, is being enhanced by generative AI to perform tasks that were once exclusive to humans. Functions like redaction, which protect private and sensitive information, are now being automated through the use of generative AI, leading to significant improvements in efficiency and work quality.
AI is also expanding the capabilities of optical character recognition by recognizing and extracting relationships, structure, text, graphs, and other document characteristics. This opens up opportunities for new functionalities such as summarizing, editing, and creating documents within the PDF format.
The potential for AI to automate entire document processes, known as intelligent document processing, is particularly promising. For instance, in the banking sector, AI could automate the review of loan applications and supporting documents, with humans only needed to handle exceptions. Similarly, in engineering and architecture, AI could streamline the creation and review of drawings and floor plans.
Contrary to popular belief, PDF is not simply a static format for sharing and archiving documents. Its evolution over time has made it highly adaptable to various workflows. With interactive features like fillable forms and the ability to customize user interactions using JavaScript, PDF has become a programmable platform. Additionally, the introduction of 3-D objects has made it the go-to format for 3-D engineering document exchange.
PDF now encompasses both structured and unstructured data, thanks to metadata tagging that enables the identification of elements like lists, tables, and headings. Intelligent document processing, powered by generative AI, has the potential to make PDF even more valuable in workflows. Its unique advantages, such as environment independence, security, trackability, and verifiability, position it as a valuable data hub between different systems.
However, achieving intelligent document processing requires two critical components. First, intelligence optimized for document analysis is needed. Second, domain knowledge is crucial for training and deploying this intelligence in specific workflows, such as loan approvals or the processing of engineering drawings or medical documents.
It’s worth noting that intelligent document processing is not a ready-to-use generative AI solution. Platforms like ChatGPT are trained on publicly available data and lack domain-specific expertise. Fine-tuning, training, monitoring, and measuring results are essential steps that require human intervention.
As AI continues to advance, it holds the key to bridging the gap between the way humans and IT systems process information. Documents, as a human-centric medium, will always be essential for creating, exchanging, understanding, preserving, and acting on information and ideas. By making documents more accessible to machine-based automation, AI-powered intelligent document processing can lead to significant breakthroughs in efficiency and decision-making.
In conclusion, the future of AI-powered document processing looks promising. With advancements in generative AI and the evolving capabilities of PDF, machines may soon be able to handle documents from end to end, transforming the way we process information and make decisions. However, human intervention remains crucial for training and fine-tuning AI systems to cater to specific industries and workflows. As we embrace intelligent document processing, we must harness the power of AI while carefully monitoring and measuring its results.
