Taxonomies vs. Ontologies for Enabling AI-Readiness

AI solutions need to be grounded in an organization’s context. It is difficult to reliably distill context from the entirety of an organization’s knowledge assets, including facts, documents, datasets, and other structured records. Without a specific directive on what matters to the organization and how the organization operates, AI solutions are likely to misinterpret important concepts or terminology in the organization, or misuse knowledge assets as appropriate or applicable inputs. Semantic models, specifically taxonomies and ontologies, can do the heavy-lifting of distilling organizational context into formal, harmonized, and actionable structures for grounding AI solutions. Leveraging semantic models for the right purpose is as important as using one at all.