Context Before Scale

Most enterprises do not suffer from a shortage of data. They suffer from a shortage of context: the operational meaning that makes evidence useful.

Small data is still difficult

A modest dataset can support consequential decisions when it is connected to process logic, formal knowledge and the corrections of experienced people.

Context as architecture

Ontology describes what exists. Process describes what happens. Formal knowledge records what should happen. Tacit capture records what practitioners learn when reality refuses the model.

AI becomes more useful when these layers are treated as infrastructure rather than annotation.