AI brand sentiment
AI brand sentiment is the tone in which AI engines describe a brand when they mention it: whether an answer recommends it, describes it neutrally, lists it among alternatives, adds a caveat or warns against it.
More than positive or negative
In an AI answer, how a brand is framed matters as much as whether the words are kind. Being the recommended choice, being one name in a list of five, and being mentioned with a note that support is slow are three different outcomes, and a single positive, neutral or negative score blurs them together. Most teams therefore sort each mention into a few framing classes, such as recommended, neutral, listed among competitors, caveated and warned against.
Example
As an illustration, a brand is mentioned in 50 answers across a set of prompts. In 12 it is the recommended choice, 20 describe it neutrally, 14 list it among several options and 4 add a caveat. Only 4 of 50 answers, 8%, carry a caveat, but if all 4 repeat the same complaint, the sources behind those answers are worth reading.
How to measure it
Use a fixed set of prompts that includes direct questions about the brand, such as "is this tool good for small teams", as well as category questions. Classify each mention, then count the share in each class per engine over several days, since answers vary from run to run. When a negative framing repeats, check the cited sources: an outdated review or a wrong fact is often the cause.
Why it matters
Mention rate and share of voice count presence. Sentiment says whether that presence helps. A brand can be named often and still lose the buyer if most answers add a caveat.
See how AI describes your brand
Get a free AI visibility audit across ChatGPT, Gemini, Perplexity and Google AI Overviews and see where you stand against your competitors.
Get your free visibility audit