Share of successful samples that mention the selected entity.
Emma Watson
in AI answers
Emma Watson is a British actor whose international public career reaches across film, screen entertainment, and broader popular culture.
Why measure Emma Watson?
A long and internationally recognized screen career makes Emma Watson a strong case for measuring unaided AI recall, prominence within bounded lists, and recall stability across repeated model queries.
An eligible audit asks models a fixed set of unaided questions without naming Emma Watson. The evaluator then checks exact and declared aliases, list position, topic coverage, and stability across repetitions. The resulting number describes only that configuration and date.
What the evaluator watches for
The single name “Emma” alone is ambiguous and is not counted without a clear reference to the person.
Prompts in the unaided standard pack do not name individual films, franchises, or roles.
A result reflects model output only — not talent, career importance, popularity, or public sentiment.
What an eligible result contains
Credit based on safe list position or a clear unranked mention.
Tested prompt categories containing at least one mention.
Stability of mentions across repeated versions of each prompt.
Emma Watson AI visibility FAQ
What is Emma Watson's AI Visibility Score?
The latest eligible score is 6/100, measured July 17, 2026. It applies only to the shown models, prompt pack, settings, and date.
Does a higher score mean greater real-world fame?
No. It means more frequent and prominent appearance inside a declared AI-model test. Fame, reputation, audience size, achievement, and sentiment are different concepts.
How often can this profile update?
Standard memory measurements are refreshed no more than every 30 days unless the model version or methodology changes. An identical fresh audit is reused and creates no new AI provider requests.



