Ontology
A shared, explicit model of the things in your business — customers, cases, products — and how they relate, so humans and AI mean the same thing by the same words.
An ontology is a formal map of your business vocabulary: the entities that exist (customer, order, case, supplier), their properties, and the relationships between them. It answers questions like 'what exactly do we mean by an active customer?' in a way both software and AI can use.
Executives should care because ambiguity is expensive. When 'customer' means one thing in sales and another in finance, every report, integration and AI assistant inherits the confusion. An ontology turns tribal definitions into shared, machine-readable ones — and AI agents perform dramatically better when the concepts they work with are defined rather than guessed.
Concrete example: a manufacturer defines 'downtime' once — which events count, which do not, how it links to machines and shifts. Suddenly maintenance reports, AI summaries and board dashboards all agree, because they all speak from the same model.
You do not need a philosophy degree or a massive project: start with the twenty nouns your business runs on, define them, and keep the list owned and current.
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Ontology
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