Auto-Classification for the Enterprise: When to Use AI vs. Semantic Models

Auto-classification is a valuable process for adding context to unstructured content. Nominally speaking, some practitioners distinguish between auto-classification (placing content into pre-defined categories from a taxonomy) and auto-tagging (assigning unstructured keywords or metadata, sometimes generated without a taxonomy). In this article, I use ‘auto-classification’ in the broader sense, encompassing both approaches. While it can take many forms, its primary purpose remains the same: to automatically enrich content with metadata that improves findability, helps users immediately determine relevance, and provides crucial information on where content came from and when it was made. And while tagging content is always a recommended practice, it is not always scalable when human time and effort is required to perform it.