Of all the challenges, applications and real-world use cases that Artificial Intelligence (AI) has been directly involved with, one of the most important and prominent is the role that it can play in managing content for enterprises. 
Content is an integral element of modern business strategy, used to help enterprises design and launch products, drive marketing, increase sales and much more. In fact, content is essential to effective customer experiences (call centre operations, customer self-service, etc.) as well as in numerous back-office processes (e.g. claims processing, underwriting, etc.). But content has long been a challenge from an information management perspective. It can be nearly impossible to find due to inadequate and inconsistent metadata attributes, limited search functionality within core business applications, and the simple fact that it is often scattered across any number of disconnected different systems and repositories.
With legacy content management systems proving to be less effective at managing modern content volumes and types, more modern content management systems providing AI capabilities have emerged to fill that void. These modern solutions can extract critical data from content and, in doing so, transform content into intelligent information that can be easily found, readily used to perform work, and always accessible.
An avalanche of content
In a recent Nuxeo survey of UK financial services companies, 80% of respondents indicated that their systems were not fully integrated and their organisations had an average of nine different content management systems in place. This is most likely very similar across other sectors, and as the importance of content has grown, so too has its volume and variety, making it even harder to manage.
In fact, the volume and types of content are growing at an unprecedented rate. Many enterprises have accumulated billions of documents and scanned images over the last 20 years. But today, some are looking to

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