Improve Enterprise AI with Semantic Content Management

In my article, How to Prepare Content for AI, I introduced some basic steps to help you prime your organization’s content for an effective AI implementation: two of those steps – structuring and componentizing – are often misunderstood or skipped because they tend to be more difficult and time-intensive. While ‘slow down to speed up’ may not sound appealing, these steps are critical for certain kinds of content to achieve scalability and maximize your organization’s return on investment with AI.  The Content Management Continuum  Before we jump in, we need to clarify that there are three major content management methods that exist on a continuum — File-Level Management, Page-Based Content Management, and Semantic Content Management.  File-Level Management results in final output of information in the form of a document or file; there is no codified structure that exists within the document, and it is meant to be consumed as a whole. Page-Based Content Management gives authors a blueprint or a template to construct a page of content.