For telecoms marketers, the value of industry media has usually been understood in human terms. A strong article reaches operators, vendors, analysts, partners, investors, employees, and competitors. It shapes opinion. It builds credibility. It gives a vendor a more trusted voice in the market than its own channels can provide alone. This remains true, but it’s no longer the whole story.
A new audience for telecoms journalism
As generative AI becomes part of how technology buyers research markets, another audience is now quietly learning from the same coverage: large language models (LLMs). Tools such as ChatGPT, Claude, Gemini, and Perplexity are increasingly being used to explain categories, compare vendors, summarise trends, and support early-stage supplier discovery. When they do that, they are not inventing the telecoms market from scratch. They are drawing on the public information layer that already exists.
This layer includes vendor websites, industry analyst commentary and reports, content from industry associations, including technical documentation, and, importantly, specialist trade media like The Mobile Network.
AI discovery is not replacing the old influence system, it’s compressing it. A buyer who once read several articles, browsed vendor websites, checked analyst views, and asked peers for perspective may now ask an AI engine to summarise the market in one answer. The sources still matter. But they are being pulled into a different synthesised interface.
For telecoms industry media, this is a powerful finding. It shows that respected sector titles are helping educate LLMs
Understanding AI discovery
The Hoffman Agency’s new report, Understanding AI Discovery in B2B Technology Markets, looks at this shift in detail. Using GEDI, our in-house Generative Engine Discovery Insights tool, we tested how vendors are surfaced across telecoms, cybersecurity, enterprise technology, and fintech. The telecoms findings were especially striking.
Across the telecoms dataset, earned media accounted for 364 citations, or 22.6 percent of all citations. That was the strongest earned-media profile of any sector in the study (we have seen earned media citations exceed 30% of overall when analysing other results). Seventy-five earned domains appeared in the AI answers, and 16 of those were reused by two or more engines. Repeated use across multiple models suggests something more meaningful: that a source is helping shape the shared information environment AI systems rely on. For telecoms industry media, this is a powerful finding. It shows that respected sector titles are helping educate LLMs.
Trade media still shapes the market
This is not about suggesting that journalism exists to feed machines, because it doesn’t. Telecoms trade media exists because the industry needs informed, independent, specialist reporting and analysis. Publications such as The Mobile Network, which remains a notable and respected voice in the sector, play an important role in helping the industry interrogate technology claims, understand market shifts, and separate substance from hype. But in an AI-mediated discovery environment, that editorial role gains an additional layer of influence. Articles written for human readers may also become part of the material AI systems use to explain the market back to future buyers.
This changes the commercial case for earned media. Coverage is no longer only a reputational asset, a visibility driver, or a validation point for sales teams. It can also become part of the source ecosystem that determines whether a vendor appears in AI-generated answers at all.
Why this matters for vendors
For vendors, the implication is simple but significant. If AI systems are increasingly used for early discovery, then being represented in the sources those systems trust becomes a strategic priority. In telecoms, our research suggests that specialist editorial coverage is one of those critical source types.
This should be encouraging for communications teams. The fundamentals of good media relations still matter: a clear point of view, credible evidence, technical relevance, and a story that helps the market understand something important. What changes is the downstream effect. A well-placed article can now influence not only the people who read it directly, but also the answer layer that sits between future buyers and the wider web.
Working together for cumulative good
However, earned media cannot carry this burden alone. Our telecoms analysis also showed that AI systems rely heavily on vendor-owned content, particularly when they need technical detail, product explanation, or category definitions. Earned media may help a vendor enter the answer set. Owned content helps the model understand what that vendor does, how it describes its capabilities, and whether its claims can be verified.
The strongest AI visibility comes when the two work together. If a vendor is described one way in trade media, another way on its website, and a third way in its thought leadership, the result is a weak signal. Human buyers find this confusing. AI systems do too.
This strengthens the need for vendors to align more closely with the categories, language, and proof points being covered in the media, then echo the same themes across their websites, sales materials, and wider marketing activity. It also creates a stronger case for working with industry media on a paid basis, not as a substitute for earned coverage, but as part of a more purposeful visibility strategy.
Sponsored insight, research partnerships, webinars, newsletters, podcasts, and other commercial formats can all help vendors build a more consistent presence in the trusted environments that buyers and AI systems already look to for context.
The telecoms trade media has always helped the industry make sense of itself. In the AI discovery era, it may also help determine how the industry is explained back to buyers. Vendors that want to improve AI visibility should therefore think beyond isolated coverage wins. They should think about sustained, credible participation in the trusted media environments that are teaching the machines what matters.
About the author: Paul Nolan is Co-MD, The Hoffman Agency. Access Hoffman’s report, Understanding AI discovery in B2B technology markets.
For more on how The Mobile Network’s media and content solutions can help your company, contact TMN’s and Sales and Partnership Director Shahid Ramzan.
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