Negative AI Search: When AI Tells Users to Avoid You

Negative AI Search: What Happens When AI Answers "What to Avoid" and What to Do About It

AI searches don't just answer, "What should I buy?"

They also answer "What should I avoid?", "Which brands have problems?", and "What are the alternatives to X?"

How your brand appears in those answers is becoming as important as how you rank for commercial queries

This is negative AI search, and most SEO strategies don't account for it. In this blog, we'll cover the topics of: 

• What Negative AI Search Means

• How Different AI Platforms Handle Negative Queries 
• Why This Is an SEO Problem, Not Just a Reputation Problem
• The Content Strategy for Negative AI Search
• What to Do If AI Is Already Saying Something Negative About Your Brand
• Measuring Your Negative AI Search Exposure   

What Negative AI Search Means

A negative AI search is any query where the user is looking for reasons not to buy, brands to avoid, or alternatives to consider.
Think:

• "What are the worst [product category] brands?"

• "[Brand name] problems" 

• "Alternatives to [competitor]"

• "Is [service] worth it?"

• "[Product] reviews complaints"

That answer, whether fair or not, becomes the default response for every user who asks the same question.

How Different AI Platforms Handle Negative Queries

Not all AI platforms respond to negative queries the same way, and understanding the differences matters for how you build your content and review strategy.

Google AI Mode is the most specific. It names companies directly, citing user-generated content from Reddit, Facebook reviews, and consumer forums. If those sources mention your brand negatively, AI Mode will surface that content. It tends to be the most authoritative-sounding because it cites sources, which gives users confidence in the answer.

ChatGPT Search is more inconsistent. It sometimes recommends a company it had just flagged as problematic in the same conversation. Source citations are often absent, which makes the responses feel less grounded but also harder to predict. A brand can appear in ChatGPT's negative answers without any clear reason tied to verifiable content.

Microsoft Copilot takes a more cautious approach. Rather than naming specific companies, it tends to list general warning signs, such as "look for companies that lack warranties" or "avoid providers who don't publish pricing". This is less damaging for individual brands but also less useful for users, which may reduce its influence on purchase decisions.

For Australian ecommerce brands and service businesses, Google AI Mode is the highest-priority platform to watch because it is the platform most users interact with, and its responses carry the most visible source attribution.

Why This Is an SEO Problem, Not Just a Reputation Problem

Brands often treat online reputation management as a PR task and topical authority in search as an SEO task. Negative AI search sits at the intersection of both, and falling between the two means nothing gets done.

The content that AI platforms pull into negative answers comes from the same sources that influence AI Overviews more broadly: review platforms, forums, news coverage, and content on your own site. The difference is that for negative queries, the weighting shifts heavily towards user-generated content and third-party reviews.

Your product pages and marketing copy carry very little weight in negative answer generation. Google is not going to cite your "Why we're the best" page when answering "What brands to avoid in this category?"

What matters is:

1. The sentiment of content on third-party platforms (Trustpilot, Google Reviews, Reddit)
2. Whether your own content addresses concerns directly and credibly
3. How much authoritative third-party coverage exists about your brand
4. Whether your entity SEO signals help AI understand your brand accurately

The Content Strategy for Negative AI Search

Monitor What AI Is Already Saying About Your Brand

Before building a strategy, you need to know what AI systems are saying about you today. Test the following queries across Google AI Mode, ChatGPT, and Perplexity:

• "[Your brand] reviews"
• "[Your brand] complaints"
• "[Your brand] problems"
• "[Category] brands to avoid."
• "Is [your brand] worth it?"
• "Alternatives to [your brand]"

Build a Presence on the Platforms AI Cites

AI Mode pulls from Reddit, Google Reviews, Trustpilot, and consumer forums far more than branded content. Encouraging genuine customer reviews on these platforms, responding to negative reviews professionally and in detail, and participating authentically in relevant forums all affect what AI surfaces.

This is not about gaming review platforms. Google's systems, as outlined in Google's helpful content guidelines, prioritise authentic, people-first signals. The goal is to ensure that the authentic record of your brand's performance is visible and representative.

Create Content That Addresses Concerns Directly

Brands that pre-empt common objections on their website give AI systems something credible to reference when answering neutral queries that tip negative. A page titled "Common questions about [product]" that honestly addresses known limitations, compatibility issues, or typical customer concerns reads as trustworthy to both users and AI.

Such content is different from defensive marketing copy. It means publishing the equivalent of "Here are the honest trade-offs of choosing us over a competitor." That kind of content, grounded in E-E-A-T principles, is what AI systems are more likely to cite.

There is often internal pushback on this approach. Marketing teams and founders resist publishing anything that acknowledges a limitation. But the reality is simple: if third-party websites are already talking about your brand's shortcomings, AI is already surfacing that content. You don't get to choose whether the conversation happens. You get to choose whether you're part of it. Controlling the narrative through clarity and honesty on your own site is how you stay in the know.

Digital PR for Brand Authority

The biggest lever in a negative AI search is the breadth of authoritative, positive coverage about your brand.

A strong digital PR strategy builds that coverage. When a brand has been covered by credible Australian business publications, industry outlets, and independent editorial sources, AI systems have a richer, more balanced pool of content to draw from.

StudioHawk's work with JobAdder is a strong example of this strategy in action. The campaign generated 58 media placements across major outlets and 38 high-authority backlinks with an average domain rating of 57, alongside a 31% increase in referring domains.

The result was a 361% increase in organic traffic and an estimated 42 million media reach. That volume and authority of external coverage make it significantly harder for a negative narrative to dominate AI-generated answers about the brand.

What to Do If AI Is Already Saying Something Negative About Your Brand

If you've run the tests above and AI is surfacing inaccurate or unfairly negative content about your brand, the response is the same as for any brand reputation challenge, but with a few additional layers:

Find the source content. AI cites sources. If a negative AI answer exists, there is source content driving it. Identify which platforms and posts are being referenced.

Respond on the source platform. A professional, factual response to a negative review or forum thread is content that AI can surface alongside the original. It demonstrates accountability and may shift the overall sentiment of the source.

Create competing, credible content. High-quality, well-sourced content from your own domain and from authoritative third parties gives AI systems alternatives to cite. The answer will not always pull from a single source.

Don't fabricate. AI search platforms are increasingly adept at identifying manufactured content, and AI-written content designed purely to bury negative results will not perform the same way as genuine coverage.

Measuring Your Negative AI Search Exposure

Traditional keyword rankings tools don't track AI answers.

You need a dedicated monitoring process, and there are now tools built specifically for this purpose.

Peec AI tracks how your brand appears across AI search platforms, showing you exactly what AI is saying about you and which sources it is pulling from. Profound takes a similar approach, monitoring AI-generated answers for brand mentions and sentiment shifts over time. Both give you the visibility that traditional rank trackers can't.

Alongside these tools, build a regular manual check:

1. Run the test queries above monthly across AI Mode, ChatGPT, and Perplexity
2. Screenshot the answers and the sources cited
3. Note which sources appear consistently in negative answers; these are your priority platforms for review building and response
4. Track changes in AI answer sentiment over time as your response strategy takes effect

This is early-stage work for most Australian brands.

The brands that build a negative AI search monitoring process now will be significantly ahead when AI search becomes the dominant interface for discovery.