- Why Earned Media Matters to AI Visibility & Why SEO Cannot Do the Whole Job - September 14, 2026
Search and PR have traditionally sat in different parts of the marketing plan. One concerned itself with rankings, websites, and traffic. The other dealt with journalists, reputation, and what appeared in the media.
AI is making that division look increasingly dated.
When somebody asks ChatGPT, Claude, Gemini, Perplexity, or Copilot to recommend companies, compare products, or explain who leads a particular market, the platform has to construct an answer from information it can find and interpret.
The first challenge for a brand is therefore familiar to anyone working in search. The company must be discoverable. Its website needs to be technically accessible, its content properly structured, and its expertise clear enough for machines to understand. There is then another question. Why should the platform trust what the company says about itself?
The Limits of Owned Content
Every corporate website has an obvious bias. A software company is unlikely to publish an article explaining why a rival product is better. A bank does not describe itself as the fourth most innovative business in its market.
Corporate content exists to present the company’s own case.
A good search strategy makes that content easier to discover and understand. It can establish a clear relationship between the company, its products, and the subjects on which it has expertise. But there is a wider information environment around every brand.
Journalists write about it, trade publications interview its executives, researchers cite its work, and customers discuss its products. Independent reports compare it with competitors. Large language models (LLMs) can draw on that material too, and this is precisely where PR becomes relevant to AI Visibility.
Research from Muck Rack’s Generative Pulse, which analysed more than one million citations appearing in AI-generated answers, found that 82 per cent came from earned sources. These extend beyond journalism to include academic, government, NGO, and other independent third-party content, but the finding is significant for PR. AI platforms are drawing heavily on information published outside a brand’s owned channels when deciding which sources to use and cite.
Where Blue Train & Mixology Meet
Blue Train Marketing and Mixology PR approach AI Visibility from different professional backgrounds.
Blue Train is a digital marketing agency specialising in the fintech sector. Its expertise spans search, website performance, content, and optimisation. It helps brands create the digital foundations that allow AI platforms to discover and understand them. Mixology works alongside Blue Train as an external partner. Through media relations, research, news, interviews, and contributed editorial, we create opportunities for companies to build credible coverage in publications they do not own or control.
Marketing and PR activities are closely related. A strong website gives an LLM a clear source of information about a business. Search optimisation helps make that information accessible. Well-planned content builds depth around the subjects a company wants to own. Earned media provides independent context around those claims.
Neither discipline can comfortably do the whole job.
A company with excellent technical SEO but no credible external profile may be easy to find yet have limited independent authority around its brand. Another business may enjoy strong media coverage but have an outdated website and a confusing content structure, which makes it difficult for search engines and AI platforms to understand what it does. AI Visibility brings these problems into the same conversation.
What We Have Seen in Practice
Blue Train and Mixology have been able to examine this through an AI visibility programme for a B2B financial services client.
Blue Train spearheaded a consumer behaviour study focused on retail banking. The research created original content for the client while providing Mixology with a strong editorial platform. We publicised the findings and built an earned media programme around them, developing editorials, bylined features, and opinion pieces for various fintech, banking, and payments publications.
During the monitored period, the client’s average AI visibility across the UK, Germany, the Netherlands, and the US increased from 5% to 14.75%. Its competitive ranking changed as well. The business moved from 107th to 3rd in Germany and from 78th to 7th in the UK. By August 2026, it ranked inside the Top 10 across all four markets.
The source analysis was even more revealing than the rankings, which showed AI responses drawing on the client’s product pages, research, and editorial material, alongside articles and coverage published by third-party industry media.
This is an important distinction because there is no evidence that a single tactic produced the improvement. The client’s digital presence was developing while its earned profile was growing. Search, content, research, and media activity worked together at the same time. The resulting AI responses contained material produced across that mix.
This is what makes the case study valuable. It’s a reflection of how AI visibility is likely to work, rather than claiming that the solution is one marketing discipline.
Why Media Authority Still Matters
Earned media becomes even more important as generative AI makes it easier and cheaper for companies to produce their own content at scale. The ability to publish, however, is quite different from having something worth saying.
Good journalism still depends on original research, informed opinion, and stories that stand up to editorial scrutiny. Securing coverage gives a company something it cannot produce for itself; independent recognition that its ideas or expertise are worth paying attention to.
For LLM discovery, this may become an increasingly valuable distinction as the internet becomes polluted with synthetic content. When producing another thousand words costs virtually nothing, the origin and authority of information become increasingly important.
PR has a role in creating that authority. Search has a role in making sure the wider digital footprint around the company is structured, visible, and understandable. The opportunity sits where those disciplines overlap.
AI Visibility Changes the Planning Conversation
This also changes the questions marketing teams should be asking. Traditional search analysis tells a company where it ranks and where opportunities exist. AI Visibility analysis can begin to show whether a brand appears when buyers ask broader questions about its market:
- Which companies does an LLM recommend?
- Which competitors appear repeatedly?
- What sources support those responses?
- Which publications are being cited?
- Does the company’s own content feature?
- Is there credible third-party information about the business around the subjects that matter commercially?
These questions can shape both search and communications strategy. If a particular industry publication repeatedly appears as a source, that becomes useful information for the PR team. If an LLM misunderstands what a company does, there may be a content or structural problem for the marketing team to investigate. If competitors dominate answers around an important subject, both teams have a reason to examine why.
This is a more useful approach, rather than treating GEO as a mysterious new branch of marketing with its own vocabulary and promises.
The fundamentals remain recognisable:
- Make useful information available.
- Structure it properly.
- Build expertise around subjects that matter.
- Earn credible independent coverage.
- Measure whether the brand becomes more visible over time.
- AI has changed where that work can surface.
A Shared Opportunity
Marketing specialists have spent years helping brands become easier to find. PR professionals have spent equally long trying to make companies worth finding. LLMs are bringing these objectives closer together.
There is no credible shortcut to AI Visibility, and no single discipline owns it. Brands need a strong digital foundation, useful content, and an external body of evidence that gives context and credibility to what they say about themselves. Our work together is beginning to show how those elements can reinforce each other.
For Blue Train, the opportunity lies in helping companies create the search and content foundations from which they can be discovered and understood. For Mixology, it lies in building the news, commentary, research, and media coverage which extends that authority beyond the company’s own channels.
The technology is new, yet the underlying problem is not. A company still has to give people, journalists, and now machines, a good reason to believe it matters.
