One of the ways companies are using Artificial Intelligence and Machine Learning in their processes can be very well understood from their adoption of a powerful content management system, called the ECM. ECMs have come a long way from being traditionally used as back office accessories to becoming the most sought after Cloud based services in the modern digital transformation journeys.
Why Companies Adopt ECM?
Organizations are slowly doing away with their paper-based systems. Today, we see at least 60 percent of the businesses deploying content management systems, also referred to as Enterprise Content Management (ECMs) across all their departments and functions. While there are numerous cost related benefits of using an ECM across a company, the greatest advantage arises from the way it brings automation to the user’s fingertips. No more fear of losing content to sabotage or natural calamities and no more administrative hassles that prevented managers from creatively spending time on looking for solutions.
How ECMs Process Content: Understanding the ECM Life cycle?
All ECMs have more or less a very similar working principle. These can be broken down into the following steps.
- Capture Content: Compiling and storing content in a digitized format using text to image conversion tools.
- Publish Content: Using ECM publishers / editors to publish content on a Cloud platform.
- Edit / Rectify Content: Auditing and modifying content online using online tracking tools to ensure mangers / auditors have complete control on the edited / modified version that can be compared to older versions.
- Archiving Content: Most ECMs are provided with an inherent ability to store information that can be backed up for future reference.
- Deletion: When ECMs get full, there is a scope of either buying more storage space on the Cloud / data servers or simply deleting obsolete content.
Now you can clearly understand the role of AI and machine learning in ECMs and how these can be applied at various stages of the ECM lifecycle to simplify the whole process.
One of the best applications of AI ML within ECM lies in the way users can implement Machine Learning capabilities to simplify content through classification, segmentation, and categorization.
For example, the content of various departments such as Marketing, Sales, Finance, IT, IT, HR, and Business Intelligence teams can be accurately segmented into separate ECM blocks. The AI component uses either text analytics or NLP to sieve through tons of information and segment the file based on keywords specific to that department.
A data-intensive industry like E-commerce or Social media monitoring could save billions of dollars by simply moving to an advanced ECM model. Apart from automated management of content, ECMs also offer advanced predictive intelligence with time-series and tree-based ML algorithms to secure data and address critical security issues related to identity management and access.
If you are pursuing a machine learning course Bangalore, don’t miss out on the opportunity to work on projects specifically designed for ECM development and integrations.
