Almost each and every business these days needs a reliable Document Management System (DMS) to store and manage all its business documents with the help of software that may be an on-premise or cloud-based system. An adequate Document Management System is very necessary to make sure that all employees are working with the most updated and relevant data available. It also helps in preventing the valuable time of your resources, which was otherwise spent in retrieving the documents that have been poorly indexed or badly archived.
As the companies expand their business, the amount of newly generated data also keeps increasing simultaneously with companies’ growth. According to research by Forbes, 15 Exabyte of data were generated worldwide in 2005 and almost 1200 Exabyte in 2010. In the current scenario, the figures have reached approximately 2.5 quintillion bytes. At this speed, the worldwide data volume is expected to increase up to 44 zettabyte by the end of the year 2020. Traditional data management systems are seen helpless in managing the high volume of data produced these days. Many leading companies such as ecommerce, healthcare companies generate large mountains of data that is just not possible to deal with traditional document management systems (DMS). But, since the last few years, artificial intelligence (AI) has been transforming conventional document management systems and opening up new horizons for the document management industry.
But the pattern in which documents are archived and stored has evolved with the technology. In the recent past, Artificial intelligence has revolutionized the different ways in which an organization can store, archive, index, process, and retrieve information. There is a drastic change in the structure in how data and documents are now stored online in the cloud, rather than in data centers offsite storage. Also, there are numerous changes in how these documents are accessed through different and latest programming interfaces (called APIs). These advancements have fueled the possibility of using document management in new and more creative ways. Artificial intelligence has become a regular part of our daily lives nowadays. Take Siri and Alexa for example!
Creating New Horizons in Document Management using AI
An interesting aspect of Artificial Intelligence is its great potential to transform businesses any business with its Machine learning and Natural Language Processing capabilities. The development of Artificial intelligence is fuelled by cloud storage solutions to a great extent in the vertical od document management or DMS software. There is a great amount of raw data in the form of documents being extracted from millions of sources and this basically lays down the foundation on which machine learning and AI stand apart. This huge volume of data is brought together to be analyzed and processed collectively. Machine learning helps Artificial intelligence and insights by observing the information collected from multiple resources. These insights then are processed and decide the actionable that can help in boosting organizational performance, resource efficiency, as well as offering greater convenience, while further excluding the redundant data, manual, and repetitive tasks.
Lets’ have a simple example, if you search any document on a desktop, you either need to know its exact location or perform a search. Artificial intelligence develops human-like interactions with machines to highly improve the tasks of storing documents in a more engaging way. This feature not only decreases the time and effort of resources but also increases overall organizational productivity. With Artificial intelligence, the management of documents becomes simpler and easier. Artificial intelligence services with the help of NLP and machine learning can drastically improve document management software, making them smarter and less time-consuming. Lets’ have a look at how AI is helping companies to perform the business process of document management spontaneously-
Data Analytics: One of the best and most interesting features of artificial intelligence in document management is the support for analytics and the value it provides for decision making through ML and NLP. Document management software uses machine learning, predictive analysis, ocr, cloud, and data visualization to retrieve insights from data present in the form of digital or physical documents. For example, various platforms like OpenText Magellan and IBM Watson provide data analytics and dashboard to covert the data and make document management work swiftly.
Automatic Data Classification: Optical character recognition (OCR) technology has been continuously changing the text recognition feature in a DMS. Artificial intelligence takes this a vertical higher by enabling it to actually read documents effectively, analyze its content systematically, index and classify them correctly, and also automate workflows in compliance with proper tagging documents. The new OCR is the perfect example of artificial intelligence integrated with sub-verticals like NLP and machine learning effect.
This system integrated with artificial intelligence can automatically identify, analyze, and process data from repeated exposure to documents, and from the actions initiated by your organizations’ employees upon the set of documents. For example, document management software powered by artificial intelligence will identify bills on its own by recognizing elements such as bill numbers or line items, etc.
Document Clustering: While documents are clustered, all the documents are collected by topics without prior classification. AI technology has helped us to make the process quite simple and easier. Document management software enables effective assigning of documents to unique topics, set their hierarchy or hierarchies are not known in advance. This enables you to understand how documents are related to one another within a wider context. It lets you make inferences and find out similarities that would not have been possible earlier. The part of document clustering is highly sensitive in the whole pross of document management. Clustering can be considered as the backbone for the efficiency of the system. The more efficiently the clustering is initiated; the better will be the processing of documents. Clustering helps the whole process in the analysis of data extracted from the documents. You can consider the example of the clustering of documents based on related categories of animals, plants, or particular projects, etc. The data clustered properly will help further in analysis and creating a database in a very effective and time-saving manner. Any document storage company will try to keep a strict eye on this part for better fulfillment of overall process.
Advanced-Data Security: Document management software powered with the esteem of artificial intelligence can easily enhance the security of your business information and protect your employees as well as customers’ data. This is one of the reasons that a particular or record management system can detect sensitive and personal identifying information (PII) very successfully. It comes with a number of other features like you can also mark documents which are required special handling or further analysis. Other than that, with the help of automatic clustering and processing, there may be no documents left in unsecured locations while waiting to be processed. It is also very easy to prevent unauthorized editing, access, viewing, or alteration of documents by securing user access with secure biometric techniques, like facial recognition, fingerprint scanners so that only the employees who have authorized access to the system can use it. Any Record management company will highly recommend the authorization access as the main feature of AI powered DMS.
With the growth of artificial intelligence, AI-based DMS are touching the new possible goals. artificial intelligence is among the leading technologies for developing a smart workplace with automated workflows that not only streamline the data management process but also increases productivity and resource value.