There has been a demand for AI in document management from the beginning of document scanners and the digitization of paper documents. Users required a simple method for indexing and categorizing numerous scanned documents.

Hence, using optical character recognition (OCR) to read the content of documents was one of the earliest applications of AI in document management. Multilayer perception (MLP) neural network classifiers were utilized by OCR to detect letters based on their shape, and the models were simple to train to function with various alphabets and fonts. Even handwriting could be deciphered by the models, albeit inaccurately.

Since then, enterprise document management systems have gradually increased and automated various tasks. For example, they developed the ability to recognize and extract metadata from structured documents. Also, they improved the relevancy and accuracy of search results. And more recently, the use of AI to document management has grown to encompass more sophisticated features, including the ability to produce insightful conclusions and forecasts based on data and text analysis.

Typical AI Enterprise Document Management Use Cases

The following are some of the most prominent and successful uses of AI in enterprise document management:

1. Automatic data extraction pulls content and metadata from documents using artificial intelligence. Examples are OCR, intelligent form recognition for structured documents (such as bills and forms), and intelligent document processing (e.g., contracts and transcripts).
2. Automatic document classification: This technique uses AI to categorize documents according to their format or content, enabling more effective storage and retrieval.
3. Intelligent search: Applying AI to a document management system’s search capabilities will make it easier for users to find pertinent documents more quickly and accurately.
4. Predictive analytics: Applying AI to examine past data and forecast future patterns, assisting businesses in making wise decisions.
5. Artificial intelligence (AI) is used to comprehend and analyze the human language used in document content to offer insightful recommendations that may enhance business outcomes.

Advantages of AI’s Usage in Document Management

The application of AI in document management has immeasurable financial advantages.

Many different businesses and industries are benefiting from it. Many instances include:

• Law businesses: Many legal firms are automating the process of reading and analyzing legal papers using artificial intelligence (AI), freeing up time for lawyers to work on projects of higher value.
• Healthcare organizations: By using AI and big data models to extract data from medical records and other documents, healthcare companies may more easily track and analyze patient data and gain insightful knowledge to enhance patient care and results.
• Financial institutions: To increase the effectiveness of their procedures and lower the risk of errors, financial institutions are utilizing AI to automate jobs like data entry and document classification.

AI is transforming into a document management force multiplier rather than simply replicating traditional document procedures in a digital version. From the processing of documents to their storage to the extraction of the information they contain, it can make every workflow step better, wiser, and quicker. It reduces waste, improves participation and collaboration, and accelerates turnaround times for typical procedures.

AI, in the following six categories, is revolutionizing document management’s administration, development, and application.

1. Computerized sorting and processing

The ability of AI to recognize what it sees and make decisions has advanced significantly in a field known as computer vision. For example, optical character recognition (OCR) technology, used in document management, allows a Document Management System (DMS) to read a document’s contents and automatically classify and process it without human interaction.

The more documents AI consumes, the better it gets at identifying and digesting information and watching how employees engage with the documents. However, there are still various intricate tasks and decisions in document management where human involvement becomes crucial; explore these facets in this guide on things humans can do better than AI to gain insights into areas where human intuition and expertise outshine artificial intelligence.

2. Data extraction

An AI-powered enterprise document management system can extract information now concealed in individual papers more precisely and rapidly.

For instance, businesses can ingest data from forms, documents, and contracts and extract key-value pairs and entities using Google’s Document Understanding AI. Also, organizations can include their schema in places where Google offers knowledge capabilities by using a new beta feature called knowledge service.

3. Grouping of documents

Web document search results have long been based on basic programming to perform cluster analysis on documents. Yet, using AI for this work results in a much better level of sophistication and accuracy.

An AI-powered DMS can more precisely categorize a company’s enormous library of documents (which is especially useful when topics and hierarchies are unknown), comprehend the connections between documents in a larger context, draw conclusions and hypotheses, and find similarities between documents. As a result, when a deep dive is needed, categorizing, organizing, and searching for company papers are made simpler.

4. Making unstructured data more orderly

Even while the modern organization collects a lot of structured data, 80% is unstructured, and 70% is a free-form language, such as emails, memos, specs, and comments.

This is not shocking because this is essentially how people communicate. Humans don’t typically interact in a structured way, and when someone attempts to impose structure on our conversations, we typically chafe and struggle against it. This may help to explain why Slack has become so well-liked. But no business can be content with keeping up to 80% of its data locked away.

5. Supporting the creation of content and documents

The procedure for developing content and documents can be significantly streamlined with the help of AI-powered DMS. Although there are currently no frontrunners in this task, software like Grammarly shows how AI may be used to “pre-edit” documents without additional human involvement.

6. Data and document security

More than ever, security is a contentious issue, particularly when it comes to private information used in the financial services or healthcare sectors. A DMS with AI capabilities is in a unique position to offer document security at scale.

AI, for instance, can be trained to recognize papers that include sensitive or personally identifying information (PII) and to mark those documents for further care. Automated processing and classification can make sure that no papers are left in unprotected areas before they are kept in a secure manner.

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