A new revenue stream for publishers: selling AI visibility as an advertising service

People looking for product recommendations or suitable service providers are increasingly turning to a language model rather than Google. Whether a brand is mentioned in the model’s response is thus becoming a new form of visibility for businesses. Publishers see this as an opportunity. They possess journalistic authority and established media brands that AI systems draw on as sources, and could translate this position into consultancy and content offerings. Corina Lingscheidt examines the potential of the brand mentions business, why its value has so far been difficult to quantify, and where the line must be drawn between editorial content and paid services.

USA Today is currently adapting its content specifically for use by AI systems. Among other things, the US publisher is investigating how articles can be technically structured so that they can be better captured and processed by language models, which content appears in Google’s AI Overviews, and which bots are accessing its own content. This reflects a trend that numerous other media organisations are now also addressing: content should no longer be optimised exclusively for traditional search engines, but increasingly for ChatGPT, Gemini, Perplexity and other AI systems as well. For publishers, this is not just about reach. At the same time, they are looking for ways to measure this new form of visibility and turn it into a marketable product for advertising clients.

A term that is currently cropping up frequently in this context is the so-called ‘brand mention’. This refers to the mention of a brand in an AI-generated response. For example, if a user asks about suitable providers for a particular service, recommended products or companies in a specific sector, the language model may name several brands and justify these with information from various sources. It is therefore becoming increasingly important for companies to know whether their brand appears in such responses and what information about them is used by the AI. This adds a further layer to traditional search engine optimisation, often summarised under the terms ‘Generative Engine Optimisation’ (GEO) or ‘AI Visibility’.

For publishers, this opens up a potential new area of business. They can start by analysing how frequently certain brands are mentioned in relevant AI responses, which competitors feature there, and which journalistic or editorial sources are used by the respective systems. Building on this, consultancy and content services can be developed whereby companies can, for example, expand their presence in a specific subject area through studies, guides, expert interviews or thematic content formats. Some international media companies already offer such services. In Germany, too, many publishers are already exploring how their editorial authority and reach can be leveraged within AI systems for the benefit of advertising clients.

For publishers, the appeal is immediately obvious. If, in future, users increasingly turn to AI systems directly for information and product recommendations, a brand’s presence in these responses may come to hold similar significance for companies as visibility on Google. Publishers have content, experts and established media brands that are used as sources by AI systems. These assets could help them offer such services with greater credibility than pure SEO agencies, which, whilst proficient in technical optimisation, do not themselves constitute a journalistic source.

It is currently difficult to assess whether this will develop into a significant revenue channel. A key reason for this is the lack of standardisation. For traditional online advertising, there are established metrics and measurement methods that allow reach and impressions to be quantified with relative clarity. With AI visibility, this is more difficult. The models’ responses vary depending on the question asked, the time, the user context and the specific model. Furthermore, different providers use different methods to track brand mentions, source attributions and visibility. There is as yet no uniform metric that can be compared with traditional advertising metrics.

This also makes the sales pitch difficult. A publisher can show companies how frequently a brand currently appears in relevant AI responses and which sources are taken into account. They can also develop content that reinforces a company’s expert authority on a particular topic. What they cannot credibly promise, however, is a specific number of mentions in ChatGPT or a guaranteed placement in an AI response. This is determined by the model in question and is subject to change at any time. Anyone who nevertheless sells AI visibility with fixed placements or guaranteed results is therefore likely to find themselves quickly faced with disappointed customers.

For publishers, there is also the question of what concrete value their services offer to advertisers. A brand mention alone does not lead to turnover. It is difficult to determine exactly how many users actually take note of such a recommendation, subsequently visit a website, and whether this results in a purchase decision. However, particularly in the case of commercial search queries, visibility within AI systems could become relevant in the long term, as users are already asking specific questions there and, in some cases, seeking recommendations. Should this trend in usage continue, the economic value of a mention could increase accordingly.

However, the impact of the ‘brand mention’ business model on publishers’ credibility must be viewed critically. When a publisher offers to improve a company’s visibility in AI systems, a clear distinction must be made between journalistic content and paid services. Editorial articles should not be produced with the aim of better positioning a specific brand in an AI response. It is, however, possible to support companies in developing transparently labelled content or to highlight their expertise in a particular subject area through studies, interviews and other formats. Particularly for media organisations, whose business model is fundamentally based on trust, this distinction should be maintained not only for legal or journalistic reasons, but also in their own commercial interest.

Whether brand mentions will ultimately make a significant contribution to publishers’ revenue is likely to depend largely on how quickly the use of AI systems develops and whether reliable measurement methods become established. As long as companies are unable to gauge the financial impact of their investments in AI visibility, the relevant budgets are likely to be treated primarily as trial expenditure for the time being. This does not mean that publishers should ignore the issue. Precisely because the market is still developing, there is an opportunity to test such offerings at an early stage and work with clients to identify which services are actually in demand and what measurable benefits they offer.