An entity is a distinct thing (a brand, product, person, or place) that machines can identify and connect facts to. Strong entity recognition is a precondition for being recommended by AI.
Models reason over entities, not keywords. If the web describes your brand inconsistently (different names, unclear category, sparse structured data), models form a weak entity: they may know you exist without knowing what to recommend you for.
Entity work is unglamorous and effective: consistent naming, clear category language on your own pages, schema.org markup, and presence in the databases and directories models treat as reference.
The signals that build a machine-readable entity
Consistent naming across your own site and every profile you control; unambiguous category language on the pages describing what you do; schema.org markup that states the same facts a human reader would take away; and presence in the databases, directories and reference sources that models treat as authoritative.
None of it is clever. Entity strength is mostly the accumulated absence of ambiguity, which is why it rewards tidying more than it rewards tactics.
How to tell your entity is weak
The signature is being known but not recommended: models can describe your product when asked directly, yet omit it from "best X for Y" answers. That gap means the facts exist somewhere but are not connected to the buying context you want to be named in.
A second signature is inconsistent naming in answers — a model calling you by a former name, a parent company, or a product line — which points at conflicting descriptions in the sources rather than at absence.