Something has fundamentally changed in how people research businesses. A growing number of prospective clients, investors, and partners no longer start with a Google search and scroll through ten blue links. Instead, they ask ChatGPT a question. They type a query into Perplexity. They glance at the AI Overview that now sits above Google's organic results. And they take the answer at face value.
This shift has created a reputation blind spot that most UK businesses have not yet addressed. You may have spent years building a strong Google presence, earning positive reviews, and publishing quality content. But if an AI assistant summarises your brand inaccurately, surfaces outdated information, or omits you entirely from a recommendation, none of that traditional work matters in the moment a potential customer asks an AI for advice.
The Wall Street Journal recently investigated how businesses are investing heavily to influence what AI chatbots say about them. Their reporting found that AI chatbot referrals grew from under one million visits in early 2024 to more than 230 million monthly by September 2025. Visitors arriving from AI platforms spend more time on sites, view more pages, and convert at significantly higher rates than traditional search visitors. The commercial value of AI visibility is no longer theoretical. It is measurable and growing rapidly.
The AI Perception Gap
There is a disconnect between how most UK businesses manage their reputation and how AI systems actually form opinions about brands. Traditional reputation management focuses on search engine results pages, review platforms, and social media. These channels remain important, but AI systems operate on a fundamentally different model.
When someone asks ChatGPT to recommend a digital agency in Manchester or the best accountancy firm in London, the response is not generated by crawling live search results. It is constructed from patterns learned during training, supplemented by web-browsing capabilities that draw from a broad range of sources. The AI does not simply rank websites. It synthesises a narrative, drawing on news articles, industry publications, forum discussions, company profiles, structured data, and third-party reviews to build a judgement of your brand.
This means your AI reputation is shaped by signals you may never have considered. A Reddit thread from three years ago in which a former employee vented their frustrations. A comparison article that positioned your competitor more favourably. An outdated Wikipedia reference. A Trustpilot profile you never claimed. AI systems treat all of these as inputs when constructing their understanding of who you are and whether you deserve to be recommended.
The concept of "perception drift" captures this challenge well. Over time, as AI models are updated with new training data, their interpretation of your brand can shift without any deliberate action on your part. A business that was once described as "innovative" might gradually become characterised as "established" or simply disappear from recommendations altogether as competitors invest in the signals AI systems prioritise.
Why Entity Recognition Matters More Than Keywords
For decades, SEO professionals have optimised for keywords. You identified the terms your customers searched for, created content targeting those terms, and built links to improve rankings. This approach still has value for traditional search, but AI systems think differently.
AI platforms understand the world through entities, not keywords. An entity is a distinct, recognisable thing: a person, a business, a product, a concept. When Google's Knowledge Graph or ChatGPT's training data processes information about your company, it is not matching keywords. It is building an understanding of your business as an entity, including what it does, who leads it, where it operates, how it relates to other entities in its industry, and what authoritative sources say about it.
This distinction has profound implications for reputation management. If your business exists as a well-defined entity across multiple authoritative sources, with consistent information, verified credentials, and clear relationships to relevant industry concepts, AI systems will have high confidence in recommending you. If your digital footprint is fragmented, inconsistent, or thin, AI systems will either misrepresent you or ignore you in favour of competitors whose entity signals are stronger.
Google Knowledge Panels illustrate this principle in action. A Knowledge Panel appears when Google's systems have enough confidence in an entity to present a structured summary in search results. Earning one requires consistent, corroborated information across multiple authoritative sources. The same principle now applies to AI-generated responses. The businesses that appear in ChatGPT recommendations are overwhelmingly those with strong, well-documented entity presences across the web.
Five Signals That Shape Your AI Reputation
Understanding what AI systems look for when evaluating brands is the first step toward controlling what they say. Based on how these systems are built and how they process information, five categories of signals carry the most weight.
Authoritative third-party mentions. AI systems place significant value on what others say about you, particularly on platforms they consider trustworthy. Industry publications, professional directories, recognised media outlets, and established review platforms all contribute to your entity profile. A single mention in a respected trade publication can carry more weight than dozens of self-published blog posts.
Structured data and schema markup. Search engines and AI systems rely on structured data to understand entities with precision. Implementing the Organisation, Person, and LocalBusiness schema on your website provides machine-readable signals that help AI systems correctly categorise your business, identify your leadership, and understand your service offerings. Without structured data, you are relying on AI to infer information from unstructured content, which introduces the risk of misinterpretation.
Cross-platform consistency. AI systems cross-reference information across sources. If your LinkedIn company page says you were founded in 2015, your website says 2016, and your Companies House listing shows 2014, that inconsistency reduces confidence in your entity data. Ensuring that core business information, including name, founding date, leadership, location, and service descriptions, is identical across all platforms significantly strengthens your entity signals.
Knowledge graph presence. Platforms like Wikidata, Crunchbase, and industry-specific databases serve as foundational sources that AI systems use to build entity profiles. Many UK businesses have never created or claimed entries on these platforms, leaving a gap that competitors may be filling. Establishing your presence in these knowledge bases provides verified, structured information that AI systems treat as authoritative.
Community validation. AI systems increasingly weigh genuine discussions on platforms like Reddit, Quora, and industry forums. Real conversations where people recommend your business or reference your expertise carry significant weight because they represent organic, third-party endorsement. This is distinct from review management. It is about being part of authentic conversations in the spaces where your customers and peers actually discuss your industry.
A Practical Approach for UK Businesses
Taking control of your AI reputation does not require a complete overhaul of your digital strategy. It requires targeted actions that build on your existing presence and address the specific signals AI systems prioritise.
Start with an AI audit. Search your business name and your key personnel in ChatGPT, Google Gemini, Perplexity, and Microsoft Copilot. Ask each platform to recommend businesses in your category and location. Document what appears. Note where you are mentioned, where you are absent, and where the information is inaccurate. This baseline reveals exactly where the gaps and risks lie.
Build your entity foundation. Claim or create profiles on Wikidata, Crunchbase, and relevant industry databases. Ensure your Google Business Profile is fully optimised with accurate categories, descriptions, and regular updates. Implement schema markup across your website. These technical foundations provide the machine-readable signals that AI systems need to understand your business as a distinct entity.
Create content that AI systems value. AI platforms prioritise content that demonstrates genuine expertise. Original research, data-driven analysis, expert commentary on industry trends, and thought leadership published on authoritative platforms all contribute to a stronger entity profile. The key is demonstrating real knowledge rather than producing keyword-optimised content that reads like every other article on the topic.
Strengthen your biographical signals. For founders and key executives, personal entity optimisation is equally important. AI systems often draw on leadership when forming opinions about businesses. Ensure that biographical information is consistent across LinkedIn, your company website, speaker profiles, and published articles. The more corroborated data points AI systems can find about your leadership team, the more confident they become in your business entity overall.
Monitor for perception drift. AI-generated responses about your brand will change over time as models are updated and new content is added to the training pipeline. Set a regular schedule to audit what major AI platforms say about your business. Quarterly checks at a minimum, monthly for businesses in competitive or fast-moving sectors. Early detection of negative shifts allows you to address the underlying signals before the damage becomes entrenched.
The UK Regulatory Context
UK businesses have a unique opportunity in this space. The Competition and Markets Authority designated Google a "strategic" player in online search advertising in 2025 and has since proposed requiring Google to give publishers the ability to opt out of having their content used in AI Overviews. This regulatory scrutiny reflects growing awareness that AI systems are reshaping public perception, demanding transparency and accountability.
The UK GDPR and the right to erasure also provide tools that can support AI reputation management. While these mechanisms were designed primarily for traditional search listings, the principles of data accuracy and the right to correct misleading information apply increasingly to AI-generated content. As regulators catch up with the reality of AI-driven brand perception, UK businesses that have already established strong entity foundations will be better positioned to benefit from new protections and frameworks.
The broader E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) that Google uses to evaluate content quality also applies to how AI systems assess entities. Businesses that invest in demonstrable expertise and verifiable authority signals are building the exact foundation that both traditional search and AI systems reward.
The Competitive Window
AI reputation management is still in its early stages. Most UK businesses have not yet audited what AI says about them, let alone deliberately influence it. This creates a window of opportunity for organisations willing to act now.
The businesses that establish strong entity signals, build consistent cross-platform presences, and create genuinely authoritative content today will be the ones that AI systems recommend tomorrow. And as AI platforms become an increasingly dominant channel for business discovery, the gap between those who invested early and those who waited will grow wider with each passing quarter.
The question every UK business leader should be asking is not whether AI reputation matters. The data has already answered that. The question is whether you know what AI is saying about your business right now, and whether you are willing to leave that narrative to chance.
About the Author
Scott Keever is the founder of Keever SEO and Reputation Pros, a Forbes Agency Council member, Fast Company Executive Board member, and Entrepreneur Leadership Network member. He has built his career at the intersection of search engine optimisation, entity optimisation, and digital reputation management, helping executives, entrepreneurs, and organisations across UK and international markets control what search engines and AI platforms say about them. Scott Keever is the author of Future-Proof Your SEO and Reputation Reset, both available on Amazon. For more information, visit keeverseo.com.
