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Being mentioned is only half the story; how AI describes you shapes the shortlist. Review the tone and caveats in real answers, trace negative framing to its sources and answer it with current proof.
What is AI brand sentiment?
AI brand sentiment is the tone and framing an AI assistant uses when it describes your company: the adjectives, the caveats and the comparisons. "A reliable choice for mid-sized teams" and "an option, though some users report slow support" both count as mentions. They do not have the same effect on a buyer.
Sentiment is only meaningful alongside accuracy. A glowing description built on outdated facts can still send the wrong customers. Review both.
How do you review what AI says about you?
Ask the questions buyers ask, save the full answers and code what you find.
| Prompt type | Example | What it reveals |
|---|---|---|
| Direct | "What is [brand] known for?" | The core description |
| Evaluation | "Is [brand] good for small teams?" | Fit and caveats |
| Comparison | "[Brand] vs [competitor]" | How you are positioned |
| Risk | "What are the downsides of [brand]?" | Negative framing and its sources |
For each answer, record the tone (positive, neutral, negative or mixed), any factual errors and the sources cited. Arrow's guide what does AI say about your business? gives a fact-checking checklist you can use alongside this.
Where does negative framing come from?
Usually from sources the AI retrieved or learned from: reviews, forum threads, old articles, comparison pages written by competitors or outdated pages on your own site. When an answer cites sources, start there. When it does not, search for the specific claim, such as "slow support" plus your brand name, to find where it appears.
Classify each negative point.
| Type | Example | Response |
|---|---|---|
| Outdated | Complaint about a feature fixed last year | Publish dated, current information |
| Accurate | A real limitation | State it honestly and explain who you suit best |
| Inaccurate | A claim that was never true | Correct the source where possible |
| Context missing | A price that excludes what is included | Clarify on your pricing page |
How do you improve sentiment without spamming?
Respond with evidence, not volume. Publishing dozens of promotional pages rarely changes how independent sources describe you. What helps is current proof: dated case studies, attributable reviews, clear documentation of fixed issues and independent coverage. See why public proof beats more content.
Answer accurate criticism honestly. A page that says "we are not the right fit for enterprise teams over 500 seats" can improve how AI describes you to the buyers you do suit. For reviews specifically, read can negative reviews change AI business descriptions?.
How do you track sentiment over time?
Use the same prompts monthly and score each answer on a simple scale. Track the share of answers with a negative caveat, the specific caveats repeated most often and whether they cite current or outdated sources. A falling count of outdated caveats is a concrete sign your corrections are reaching the sources AI uses.
Sources and editorial scope
Reviewed October 5, 2026. Platform-specific statements link to the documentation beside the claim. The workflows and examples are Arrow AI editorial guidance. AI answers vary between runs and change over time; studies cited here describe their own samples. Fictional scenarios illustrate a method; they are not customer results, measured demand or evidence of ranking gains.
Part of AI Share of Voice. Explore the Arrow AI visibility platform or request a free audit to see how often AI includes your brand today.