What happens to your brand when AI gets it wrong

Being the brand that AI surfaces when someone asks the right question is a good place to be. It means your company has built enough authority and digital presence for a model trained on vast amounts of online information to identify you as a useful answer. That doesn’t happen by accident. It reflects the time and effort required to build a reputation, publish useful information, deliver well-structured content across multiple formats, and create a clear understanding of what your business does.

Customers are now asking ChatGPT, Gemini, Claude and Perplexity which software to buy, which companies to trust and which services are worth considering. Those answers influence decisions before someone visits a website or speaks with a salesperson. AI has become another platform for brands to be discovered and evaluated.

The opportunity is significant, but so is the challenge. When AI recognises your brand, the question is whether it understands your brand correctly.

AI mistakes quickly become brand problems

AI systems are designed to provide helpful answers, but they can sometimes present incorrect information with complete confidence. A product feature can be inaccurately described, a company can be confused with a competitor or a brand with a similar name, and outdated information can appear as though it is still current. 

Unlike a journalist, AI cannot be sent a correction email. Unlike traditional search, there is no single page that can be updated to change every response. AI-generated answers are created from a combination of sources, so brands need to carefully consider the information available about them across the web. Brands should prioritise clear messaging and credible third-party coverage, which both play a role in shaping how your business is understood.

Trust is the opportunity behind AI uncertainty

EY's 2026 UK AI Sentiment Index found that 74% of UK consumers had used AI in the previous six months, while only 14% felt comfortable with fully autonomous AI systems. People are willing to use AI, but they still want confidence when information affects important decisions.

That gap creates an opportunity for brands that communicate clearly. Customers are looking for speed and answers they can rely on.

Research from Rithum found that 58 per cent of UK and US shoppers would lose trust in a retailer or brand if an AI tool provided incorrect product information. 16% said they would avoid purchasing altogether after a poor AI recommendation. The findings highlight that customers do not always separate the technology from the organisation behind it. When AI provides a poor experience, your brand can still be held responsible.

Skyword's 2026 research found that when AI-generated information conflicted with a brand's own messaging, only 29 per cent of consumers immediately trusted the brand. More than half looked elsewhere to verify what they had been told.

Consistency is becoming a competitive advantage, so your first port of call should be making sure your brand messaging is consistent across your website, owned channels and third-party coverage. With this, you will provide a reliable and recognisable story, giving both customers and AI systems greater confidence in what they represent.

Reputation is becoming machine-readable

For years, companies have established credibility through media coverage, expert commentary, research, customer stories, and valuable content. These activities help journalists and audiences understand a company and its importance. Today, they also assist AI systems in learning about brands.

This doesn’t mean creating content solely for machines. Effective communication principles haven’t changed: strong brands are built on expertise, relevance, and trust. However, information now spreads through more channels before reaching the audience.

A respected article, expert interview, or a well-maintained company profile can shape public perception and enhance the information available to AI. I see this most with tech companies whose products are difficult to explain. If a business can't describe its own technology clearly, AI will happily do it for them, and not always accurately.

What brands can do now

Start by auditing the sources AI is actually drawing from, because the fix depends entirely on where the problem lives.

Some of what AI surfaces is owned: your website, product pages, LinkedIn, press releases, and sales collateral. If this is wrong or outdated, it's the easiest thing to fix. There's no excuse for a stale pricing page or an unclear product description sitting on your own domain and misinforming an AI model. This is fully within your control, so treat it as the first pass.

Some of it is earned: journalist coverage, analyst reports, industry roundups, and third-party comparison sites. This is harder to correct, and it can't be edited directly. If a model is repeating an inaccurate description that traces back to a piece of press coverage, you won’t fix it with a blog post. Picking up the phone to reach out to the journalist or publication is the best approach. Offer a briefing or updated information, and get the correction made at the source. This is a relationship-building exercise, not content production, and it's often the piece brands skip because it's slower and less within their direct control.

Knowing which bucket a problem falls into changes what fixing it looks like.

On quality versus volume: this doesn't mean publishing more; it means being deliberate about where authoritative, current information lives and keeping it up to date. That means:

• Your website and core product pages are the anchor. They should be the most accurate, up-to-date version of your story anywhere, because they carry the most weight as a controllable source.

• Don't let your blog become a graveyard of outdated posts. A quarterly review to flag and update anything related to pricing, features, positioning, or competitors is as valuable as a steady stream of new posts.

• Prioritise content that demonstrates expertise over that which exists for volume. These could include commentary and original research, which do more to shape how AI (and people) describe you than generic explainer pages.

None of these solutions works as a one-off. You need to adopt them as an ongoing discipline to see long-term impact.

The story still matters

AI platforms have changed how people find information but not the reasons behind brand trust. The difference is that your company's first impression may now come from an AI-generated answer rather than a website or article.

Showing up accurately in AI answers is quickly becoming one of the clearest signs of a well-run brand. You can't control everything an AI system says about you but you can control the story it's working from. When you get that right, it won't matter where someone first hears about you. The story will still be yours.

If you're not sure how AI is currently describing your business, or need support building a strategy to close the gaps, that's the kind of work we do at YourStory PR. Our services include helping brands optimise their presence for relevant AI models. Get in touch and we'll show you what the models are saying about you.