Enterprise AI Architecture Series: How to Extract Knowledge from Unstructured Content (Part 2)

Our CEO, Zach Wahl, recently noted in his annual KM trends blog for 2025 that Knowledge Management (KM) and Artificial Intelligence (AI) are really two sides of the same coin, detailing this idea further in his seminal blog introducing the term Knowledge Intelligence (KI). In particular, KM can play a big role in structuring unstructured content and make it more suitable for use by enterprise AI. Injecting knowledge into unstructured data using taxonomies, ontologies, and knowledge graphs will be the focus of this blog, which is Part 2 in the Knowledge Intelligence Architecture Series. I will also describe our typical approaches and experience with mining knowledge out of unstructured content to develop taxonomies and knowledge graphs. As a refresher, you can review Part 1 of this series where I introduced the high-level technical components needed for implementing any KI architecture.