AI brand sentiment is the tone an AI answer takes when it describes your brand: positive, neutral or negative. To fix negative brand sentiment in AI, find the answers that describe you badly or wrongly. Then open the sources they cite, and correct or add to them. You cannot edit the answer itself.
ChatGPT, Gemini, Perplexity and Google AI Overviews, the AI summary above some Google results, write from the web pages they read. Google itself says "AI Overviews can and will make mistakes" (Google Search Help, checked 15 Oct 2026). An old review or a forum complaint can become a sentence a buyer takes as settled.
What is brand sentiment in AI answers?
Brand sentiment in AI answers is how an AI assistant talks about your brand when it names you. A positive mention recommends you or praises a quality. A neutral mention lists you without a view. A negative mention warns buyers off, repeats a complaint or puts you below a rival.
Two problems often travel together. One is tone, such as "known for slow delivery". The other is accuracy, such as an old price or a product you no longer sell. Check both.
Sentiment applies only when you are named, and how often that happens is your AI visibility. If AI leaves you out, read why ChatGPT doesn't mention your brand. Social media sentiment is a separate thing, as brand monitoring in AI answers explains.
How do you find negative or wrong descriptions of your brand in AI answers?
Ask the questions your buyers ask, on each engine, and read every sentence that names you. One answer is not enough, because answers vary between runs.
- 1. Write two sets of questions. Unbranded ones, such as "best sunscreen for oily skin under ₹500", show whether AI recommends you. Branded ones, such as "Brand X vs Brand Y", show how it describes you.
- 2. Ask each engine 3 times. Use ChatGPT with web search, Gemini, Perplexity and a Google search that shows an AI Overview. Ask from your market, in a new chat each time.
- 3. Log the tone with the sentence. Mark each mention positive, neutral or negative, and copy the exact sentence. The spreadsheet method has a column for it.
- 4. Check claims against a fact list. Keep your prices, products, policies and delivery areas in one place, and mark any claim that does not match.
- 5. Open the sources. Perplexity gives numbered citations to the original sources (Perplexity Help Center, checked 15 Oct 2026). Gemini shows a Sources button when it gave links (Gemini Apps Help, checked 15 Oct 2026). AI Overviews link to supporting pages (Google Search Help, checked 15 Oct 2026).
- 6. Split by language. In India, ask in English and in Hinglish (Hindi and English typed in English letters), and log them apart.
Why does AI describe a brand negatively or wrongly?
AI answers repeat what the engine reads. With web search on, the AI first runs its own searches for the question, a step called query fan-out. If the pages it finds about you are old or angry, the answer reflects them. Google says AI responses may include mistakes (Google Search Help, checked 15 Oct 2026). Even so, many errors trace back to a source you can find.
Those sources are often not your own site. In August 2026, answers from India in our AI shopping study cited reddit.com in 106 of 480 answers and youtube.com in 100. In the October 2026 re-run, amazon.in was cited in 132 of 479 answers and flipkart.com in 82.
- Old pages: a review of a product you have changed, or a listing with last year’s price.
- Complaints that rank: a forum thread or one-star review that matches the buyer’s question.
- Missing facts: if your site does not state a price or policy plainly, the AI fills the gap from other pages.
- Comparison pages: lists and "X vs Y" articles that rank a rival above you.
- Name confusion: a brand with a similar name whose reviews get mixed with yours.
- Blocked crawlers: an engine cannot read pages its crawler is blocked from. OpenAI says OAI-SearchBot is used to surface websites in ChatGPT’s search features (OpenAI crawlers, checked 15 Oct 2026).
Which negative patterns show up in AI answers, and what fixes each?
Most negative or wrong answers fall into a few patterns, each with its own fix.
| What the answer says | Where it usually comes from | What to fix |
|---|---|---|
| An old price, or a product you no longer sell | Old listings, old reviews or old pages on your site | Update your site and listings. Ask reviewers to add an update note. |
| A complaint stated as fact, such as slow delivery | Forum threads and one-star reviews | Fix the real problem, reply in public and publish your delivery times. |
| "A budget option" for a premium brand | Lists that place you in the wrong price band | Publish a clear price page. Ask list owners to correct the band. |
| A rival ranked above you for a use case | "X vs Y" articles and roundups | Get reviewed on the lists the answer cites, and publish a fair comparison. |
| A fact from a brand with a similar name | Pages about that other brand | Use one consistent name, and an about page with founders, city and year. |
| "Not available in India", or a wrong delivery area | No page that says where you sell | State your markets, delivery areas and marketplaces plainly. |
How do you fix negative brand sentiment in AI answers?
Fix the source, not the answer. You cannot edit an AI answer, so the work is on the pages the engine reads.
- 1. Fix what is real. If buyers complain about delivery or a product, change that first. A corrected page cannot outweigh a live problem.
- 2. Correct your own site. State prices, products, policies and company facts in plain sentences. Google advises that structured data match the visible text on the page (Google Search Central, checked 15 Oct 2026). Depra AI's own AI facts page is one example of a fact sheet.
- 3. Update listings and profiles. Correct every marketplace listing. Google lists up-to-date Merchant Center and Business Profile information as a best practice for its AI features (Google Search Central, checked 15 Oct 2026). See our Amazon and Flipkart checklist.
- 4. Ask other sites to correct errors. Send the author of an outdated review the correct fact and your source. Ask for a correction, not a better verdict.
- 5. Reply to reviews and threads. Answer in public with facts, dates and the fix you made, on the page the AI reads.
- 6. Earn new, honest sources. Ask real customers for reviews, and get tested on the lists and videos that answers cite.
- 7. Use the reporting routes. You may be able to claim your Google knowledge panel and suggest changes (Google Knowledge Panel Help, checked 15 Oct 2026). Not every panel can be claimed. Under an AI Overview, the thumbs-down icon lets you report a problem (Google Search Help, checked 15 Oct 2026).
- 8. Keep AI crawlers allowed. Check your robots.txt with the AI crawler checker.
How do you improve brand sentiment in AI search results over time?
Measure it the same way every period, over many answers. One good screenshot after a fix proves little, because answers vary between runs.
Mark each mention positive (100), neutral (50) or negative (0), and average them. With made-up numbers, 30 positive, 15 neutral and 5 negative mentions score 75. Write the number of mentions next to the score.
Track the sources behind negative answers too, and check whether they change after your fixes. Sentiment work is one part of generative engine optimization, and our GEO best practices cover the rest.
- Compare like with like: the same questions, engines, language and market in both periods.
- Expect no guarantee: fixing a source makes a better answer more likely, not certain.
How does Depra AI measure brand sentiment in AI answers?
Depra AI asks your buyers' questions to four AI engines from inside your chosen country and stores every full answer. ChatGPT with web search, Gemini and Google AI Overviews are checked daily. Perplexity is checked weekly on Starter, Growth and Scale, and daily on Enterprise.
An AI model reads each stored answer. For every tracked brand it names, it records the order of first mention, the sentiment, a verbatim quote and a confidence level. Sentiment is positive, neutral or negative. A mention without a quote, or below 50% confidence, does not count. The methodology has the full rules.
- Score: positive 100, neutral 50 and negative 0, averaged across mentions, for you and each competitor, on every plan. Metrics has the formula.
- Breakdowns: on the Depra AI MCP server, get_sentiment_report splits mentions by engine, topic and time, with the words used most. get_brand_insights gives the themes behind positive and negative sentiment.
- Perception and facts: the qualities AI ties to each brand, and claims checked against your fact list over the last 28 days. See brand perception and facts.
- Branded questions: left out of scores by default, but you can add them and read every answer they get.
- Languages: English and Hinglish, with multi-language support, in any of 40 markets.
- Sources: every cited website, labelled by type. From Growth up, the citation gap analysis lists the sites that mention competitors but not you.
What Depra AI does not do
Depra AI shows what AI answers say. It does not change an AI answer, write content or edit your website, and it cannot guarantee that an answer changes. It sends no alerts, and it does not track social media.
Run the free AI audit to see which of 4 AI engines name you for 5 buyer questions, with no signup. For ongoing tracking, see Depra AI pricing: Starter, Growth and Scale start with 7 days free, no card needed. Or book a demo, a free 15-minute call where the Depra AI team sets up your project.