How AI is Transforming Document Processing
By Maxime Vermeir, Senior Director of AI Strategy at ABBYY
Interest in artificial intelligence has boomed this year following the popularization of generative AI tools like ChatGPT, with many organizations scrambling to incorporate advanced AI platforms into their operations. As technologies like machine learning and large language models (LLMs) enable effective use of vast quantities of data, the implications of artificial intelligence on day-to-day workflows become increasingly visible.
However, AI has been changing the way we work for some time, such as with essential office tasks like document processing.
Many organizations rely on optical character recognition (OCR) software to convert different types of documents, including scanned paper documents, PDF files, unstructured tables, and other images into digital formats so the data can be searched, edited, and used by enterprise systems to conduct business.
But OCR has its limitations. It doesn’t really understand the information it is extracting or gain any meaning from it. This is where artificial intelligence can be leveraged to provide actionable insights through an even more intelligent solution: intelligent document processing (IDP).
AI-powered IDP has been a game changer. It enables straight-through processing of documents by automatically capturing, extracting, and processing the data embedded in them – in any process and in any industry. It enhances accuracy by cross-referencing extracted data with company databases, systems of record, and contextual information.
For example, it can be used to automate an entire accounts payable process by recognizing invoices, matching them to purchase orders to verify the amounts/vendor details, and then forward the bill to finance for payment. This reduces the need for manual data entry and minimizes human error, with most companies benefiting from a 90% improvement in invoice processing times and a 400% increase in employee productivity. With straight-through processing, invoices that used to take one-to-two days to process for payment can now be completed in less than an hour.
Now, let’s take a deeper look at the ways that AI is transforming document processing and putting businesses’ information to work:
1. Sophisticated understanding:
AI allows document processing to go beyond simple character recognition and enables comprehension of the text and language being converted – sentiment analysis, content categorization, context, and summarization, which are all vital to automating document processing. Unstructured data is identified, extracted, and recognized with unprecedented accuracy, and the technology operates like a human brain, quickly adapting to changing input and generating the best possible outcomes. Documents can be in multiple languages, formats, and varying layouts. Some IDP software can recognize as many as 200 languages including Arabic, Japanese, and European languages – perfect for global companies operating in multiple regions.
2. Document Classification:
IDP uses machine learning models to classify documents into different categories based on their content, layout, or other characteristics. Invoices might be categorized as “Invoices”, contracts as “Contracts”, or job enquiries as “Job Applicants”, and so on. It’s particularly useful for tasks like sorting emails, processing onboarding applications, and managing large sets of incoming documents.
3. Structured and Unstructured Data:
IDP is capable of handling both structured and unstructured data. It can process complex forms, tables, invoices, contracts, and other types of documents, extracting data in a structured format. IDP is regularly added to robotic process automation (RPA) platforms to enable the software robots to process unstructured data.
4. Sentiment Analysis:
AI can analyze text to determine the sentiment or emotion expressed in a document just like a human. This is valuable in customer service interactions, market research, and understanding user feedback. By incorporating natural language processing (NLP) the technology can interpret the context of the information it is reading. For example, is the word “jaguar” referring to a large cat or a car? Or is the word ‘Sue’ referring to a person or a legal action?
5. Anomaly Detection:
AI algorithms can identify unusual patterns or discrepancies in documents, which is valuable in fraud detection, compliance, and risk assessment. This may then be flagged for human evaluation – called human-in-the-loop (HITL) which provides a basis for continuous learning to ensure the same mistake will not be repeated.
6. Compliance and Regulation Monitoring:
AI can scan documents for compliance against specific pre-set business rules and highlight any potential violations, helping organizations maintain legal standards. In addition, AI can also be used to review and analyze contracts to extract key clauses or pleadings.
7. Automation of Workflows:
Document processing that incorporates AI can be used to create intelligent workflows, where documents are automatically routed to the right people or departments based on their content or context. For example, job applications will be sent to HR. It can also facilitate real-time collaboration on documents, suggesting edits, providing feedback, and ensuring consistency. The IDP platform can be easily integrated into your existing business system, such as ERP, or CRM.
8. Adaptability and Learning:
As mentioned, IDP systems use AI to learn from user interactions and feedback – human-in-the-loop (HITL) input. Over time, this can improve the accuracy and understanding of specific document types, making them adaptable to changing document formats and content structures that may be specific to a particular industry. Also, as business operations grow, the volume of documents to be processed will increase, but AI-driven IDP solutions can easily scale to handle larger document volumes without a proportional increase in labor costs.
Overall, AI is revolutionizing document processing by automating tedious tasks, improving accuracy, and providing powerful insights from large volumes of data. It is particularly beneficial for industries that handle high volumes of paperwork such as financial services, healthcare, logistics, and legal. Moreover, with new low-code/no-code AI platforms, citizen developers can deploy IDP technology in a matter of days without the need for massive IT infrastructure support and maintenance on the client’s side.
Using AI in document processing helps organizations improve experiences for both customers and employees leading to cost savings, increased efficiency, higher revenue, and better profit margins.
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