The Role of AI in the Semantic Layer

Two significant recent trends in knowledge management, artificial intelligence (AI) and the semantic layer, are reshaping the way organizations interact with their data and leverage it to derive actionable insights. Taking advantage of the interplay between AI and the semantic layer is key to driving advancements in data extraction, organization, interpretation, and application at the enterprise level. By integrating AI techniques with semantic components and understanding, EK is empowering our clients to break down data silos, connect vast amounts of their organizational data assets in all forms, and comprehensively transform their knowledge and information landscapes. In this blog, I will walk through how AI techniques such as named entity recognition, clustering and similarity algorithms, link detection, and categorization facilitate data curation for input into a semantic layer, which feeds into downstream applications for advanced search, classification, analytics, chatbots, and recommendation capabilities. Understanding the Semantic Layer The semantic layer is a standardized framework that serves as a bridge between raw data and user-facing applications by organizing, abstracting, and connecting data and knowledge from structured, unstructured, and semi-structured formats.