Summary Why it matters Category clarity Evidence Four routes Playbook Measurement Who we are
Babel | Telecoms | 2026

Known, understood, chosen

How telecoms brands should think about reputation for both humans and machines.

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Built on the Mental Av-AI-lability Index 400 B2B decision-makers Four LLMs audited
87%

of buyers chose a vendor they already knew for their last large B2B tech purchase

32%

of those who chose a new vendor discovered it through an AI tool

94%

of enterprise purchases now involve AI at the vendor evaluation stage

2

consideration sets to win: the machine shortlist and the human one

Executive summary

The new shortlisting problem

Telecoms brands are no longer competing for a place in one consideration set. The traditional buying journey is changing, and companies across the sector increasingly need to win across two connected but distinct moments.

First, they need to be visible to the machines helping buyers research the market. Then they need to be credible, memorable and regularly visible to the humans deciding which suppliers deserve serious consideration.

Babel's recent Mental Av-AI-lability Index showed that brand familiarity still matters a great deal. 87% of the technology buyers we surveyed selected a vendor they were already familiar with when making their latest large B2B tech purchase. But among those who chose a new vendor, 32% discovered the brand through an AI tool, more than through traditional search, analyst reports, word of mouth or events.

The findings make clear the value of brand visibility.

You need to be at the forefront of your buyer's mind, which isn't an overnight process. And you need to combine that with optimised visibility for LLMs.

Mental availability

The likelihood that a buyer will think of a brand when a relevant buying situation arises. It determines whether a brand comes to mind at all.

AI availability

The likelihood that AI tools will surface or recommend that brand when a buyer uses them to research the same situation. It influences whether a brand enters the machine-generated consideration set.

The two are increasingly connected, but they are not the same thing.

The new buying journey

AI discovery first, human validation second

The machine builds the longlist. The humans decide who survives it. A brand has to be retrievable at the start and reassuring at the end.

Machine consideration set
Human consideration set
  1. 01

    Buyer need

    A specific problem surfaces, such as route diversity or private 5G.

  2. 02

    AI-assisted discovery

    The buyer asks an LLM who the credible vendors are.

  3. 03

    Machine shortlist

    Brands the model can find, understand and corroborate make the list.

  4. 04

    Human validation

    The buying committee tests each name against memory, reputation and risk.

  5. 05

    Commercial shortlist

    Only the brands that feel safe enough reach procurement.

  6. 06

    Purchase

    The decision is made, usually in favour of the familiar.

Why telecoms is different

Reputation matters more than ever

Telecoms is a sector where buying decisions are high-risk, technically complex and often shaped by legacy relationships. Whether a company is selling backbone infrastructure, OSS/BSS, private networks, cloud connectivity, data-centre interconnection or network equipment, the buying committee still needs a significant level of confidence. Nobody wants to take an unnecessary risk with critical infrastructure. As the saying goes, 'no one gets fired for buying IBM'.

For those of us responsible for how brands show up, however, pursuing fame is no longer enough, if it ever was. Our research makes clear that now, more than ever, we need to ensure our brands are also famous for the right things.

This is not a call to chase AI visibility at all costs, or to throw more PR and marketing at the problem in the hope of being found. It's a moment to pause, look honestly at where your brand stands today, and decide what it will take to be better known, better understood and more confidently chosen.

Famous, but famous for what?

Telecoms has a strange relationship with awareness. The sector boasts some of the most recognisable brands in the world. Consumer operators, national incumbents, global hardware vendors, fibre providers and data centre companies are often deeply familiar to their customers and the wider market. But familiarity can be misleading.

A buyer may recognise a mobile operator instantly, but not think of it when looking for subsea connectivity, cloud interconnect or private networks. A CTO may know an equipment vendor for RAN, routing or coherent optics, but not associate it with newer priorities around edge or network modernisation. Brand awareness doesn't necessarily translate into association during a buying process.

This has always mattered, hence the decades of history the B2B marketing discipline now boasts. But it matters more when AI becomes a larger part of the vetting process. Broad portfolios, fragmented product lines and generic language around 'transformation', 'connectivity' or 'digital infrastructure' make it harder for machines to associate brands with specific buyer problems. They make it harder for a machine to understand what a company is genuinely authoritative on. And they mean that committees have to do the work of interpreting propositions all over again.

Category clarity

What makes telecoms brands easier to find and choose

A specific, repeated and well-evidenced proposition travels further. It shows up more clearly in search, media coverage, analyst commentary, AI responses and internal buyer conversations. It gives the market a simpler job: knowing when to put the brand in the frame.

That doesn't mean telecoms companies need to make themselves smaller. Many of the strongest brands in the sector are broad for good commercial reasons. The point is to organise around the buying situations and needs that matter most to customers, in other words the category entry points for each individual proposition.

Category entry points are the specific buying situations, needs or problems that prompt a buyer to consider a category and, ultimately, particular brands within it. For a telecoms brand, that might mean 'I need more resilient international connectivity', 'I need private 5G across an industrial site' or 'I need to connect our data centres to multiple cloud providers'. The stronger the association between a brand and these situations, the more likely it is to enter consideration when that need arises.

Connectivity for which workloads, routes, users and risks?

Infrastructure for which geographies, customers and use cases, and what kind: data centres, networks, cloud, edge or something else?

What does that mean in practice? The capacity, latency, automation, resilience, power and network architecture needed to support AI workloads?

The same logic applies across the ecosystem. A consumer operator needs to make its enterprise capability visible beyond the consumer halo. A national incumbent needs to connect trust and scale to new demand areas like AI, resilience, sovereignty and data-centre growth. An equipment vendor needs to translate engineering credibility into market-level relevance. A software provider needs to connect technical language to commercial outcomes. A specialist backbone provider needs to build repeated association with a narrow, valuable problem.

Fundamentally, we need to pursue programmes that raise awareness, but that also help both humans and machines know what to know a brand for.

Proof

Claims do not travel. Evidence does.

Category clarity only matters if the market can believe it. Telecoms is full of similar claims. The network is resilient. The platform is flexible. The infrastructure is sovereign. The architecture is open. The proposition is AI-ready. The solution is scalable, secure and future-proof.

The problem is that almost every competitor can say something similar. The language may be right, but on its own it is rarely enough to help a brand stand out, to buyers or to machines.

AI visibility depends heavily on what can be found, understood and corroborated. If a company wants to be associated with route diversity, private networks, Open RAN, BSS modernisation or AI infrastructure, there needs to be a visible evidence trail behind that claim.

These are not just campaign assets. They are the proof points that help machines understand what a company is genuinely authoritative on:

  • Network expansion announcements
  • Capacity upgrades
  • Customer deployments
  • Performance data
  • Interoperability testing
  • Analyst validation
  • Standards work
  • Technical explainers
  • Proprietary research

This changes the strategic value of everyday PR activity. But evidence alone can be dry, and not every piece of evidence deserves a press release.

Why thought leadership still matters

We've talked before about brands that are remembered being the ones that are chosen. But buyers won't trust or remember brands that constantly push sales-focused copy at them. They aren't just looking for suppliers with technical capability. They are also trying to make sense of a market being reshaped by major drivers: AI demand, data-centre growth, subsea resilience, network sovereignty, energy constraints, automation and new monetisation models.

Strong thought leadership helps interpret those shifts. It gives the brand a human voice, a point of view and a reason to be part of the conversation. It gives machines clearer signals about the issues a company is consistently connected to.

It's also worth noting that while good thought leadership earns trust, it also ranks well on LLMs. Journalists favour thought leadership over promotional content, so a successful thought leadership campaign puts you in more journalists' articles, which in turn rank highly with LLMs.

The strongest influence programmes do both. They build the evidence that proves the brand can solve a problem, and provide the perspective that explains why the problem matters now.

Four routes to relevance

What the quadrants reveal about telecoms brands

Babel's Mental Av-AI-lability Index is most useful when treated as a diagnostic tool rather than a rigid ranking. Each quadrant reveals a different gap between being known, being understood and being chosen. In telecoms those gaps are especially revealing, because the market contains both famous generalists and highly technical specialists.

Some brands are deeply familiar to buyers, but too broad or fragmented to be consistently retrieved by AI for specific use cases. Others are technically specific enough to show up in machine-generated recommendations, but not yet familiar or trusted enough to feel like safe choices for a human buying committee. Each quadrant points to a different communications job to be done.

Human recall
High human | Low AI

Sleeping Giants

Known, but not always understood. Authority is hard to retrieve.

 High human | High AI

Titans

Strong on both axes, but fame can become detached from relevance.

 Low human | Low AI

The Untapped

Focused opportunity, not broad awareness. Focus before fame.

 Low human | High AI

Algorithmic Disruptors

Understood by machines, not yet trusted by committees.
AI recommendation
Strong recall | Strong recommendation

Titans

The job: defend category meaning, not just fame.

Titans are telecoms brands with strong human recall and strong AI visibility, but their scale can make it harder to maintain a clear association with specific buying situations. This group includes major operators, digital infrastructure leaders and data centre brands. They benefit from scale, visibility, enterprise presence, analyst attention, customer proof and years of accumulated market activity.

The risk for these brands isn't invisibility. It's that their communications become too vague. Large telecoms brands often span consumer, enterprise, wholesale, IoT, cloud, security, managed services and infrastructure. That breadth can be commercially powerful, but it can also make the brand harder to associate with one clear buying situation. A Titan may be known by everyone, yet if its portfolio keeps expanding, buyers and AI systems may struggle to understand what it is most authoritative on now.

Defending meaning means using strategic announcements, executive commentary, research, analyst engagement and owned content to keep reinforcing the specific categories the brand wants to lead. It also means checking how AI tools are describing the business, because a brand can invest heavily in new capabilities while still being understood through older market narratives.

High familiarity | Weaker retrievability

Sleeping Giants

The job: turn reputation into category-specific authority.

Sleeping Giants are telecoms brands that buyers already recognise, but that are not consistently retrieved by AI for specialist or emerging use cases. This is a classic telecoms problem. Many established providers have enormous technical substance, but that substance can be difficult to find, inconsistently described or buried behind complicated brand architecture.

The company may have the capability, but whether the market can easily understand, repeat and verify its relevance to a specific buying situation is another issue. That might be wholesale connectivity, cloud interconnect, private networks, subsea resilience, fibre infrastructure, data-centre access, cybersecurity or digital infrastructure. The brand is known, but not connected clearly enough to the problem now being researched.

The challenge is to become easier to understand rather than to shout louder. That means simplifying proposition language around priority buying situations, creating clear source-of-truth pages for key capabilities, using earned media to reinforce specific category entry points, connecting corporate announcements to strategic growth areas, and aligning product, corporate, sales and executive messaging.

Strong recommendation | Weaker recall

Algorithmic Disruptors

The job: convert machine recommendation into human trust.

Algorithmic Disruptors are specialist telecoms brands that AI systems can readily understand and recommend, but that lack the familiarity or reassurance needed to win human buyers. This may be the most commercially interesting quadrant for challengers. In a world of AI-assisted research, a technically specific provider can enter buying conversations that its historic brand awareness would not have unlocked.

That could be a wholesale fibre provider, specialist backbone operator, cloud connectivity platform, private networks integrator, data-centre interconnection specialist, OSS/BSS platform or network automation provider. These companies get surfaced because they map neatly to a specific buyer prompt: route diversity, data-centre connectivity, Open RAN integration, cloud interconnect, BSS modernisation, private 5G or network automation.

But being recommended is not the same as being selected. Telecoms buyers still need reassurance that the provider can deliver, scale, support critical services and survive procurement scrutiny. Converting recommendation into trust means building customer and partner proof, investing in analyst relations, increasing executive visibility and using trade media to build repeated familiarity through thought leadership. PR has a very specific role here: make the company feel as credible to human buyers as it appears relevant to AI systems.

Low recall | Low recommendation

The Untapped

The job: choose one territory. Focus before fame.

Untapped telecoms brands have both low human recall and limited AI visibility, which makes broad awareness campaigns a poor use of resources. For many smaller or emerging telecoms companies the instinct is to respond with a broad awareness campaign, and in a sector as complex and crowded as telecoms that usually spreads resources too thinly.

An early-stage private networks provider, regional fibre challenger, neutral host specialist, edge infrastructure start-up, niche OSS/BSS module vendor, network automation start-up or specialist systems integrator does not need to become famous across the whole telecoms market overnight. It needs to become clearly associated with one commercially valuable problem: indoor mobile coverage for complex venues, private 5G for industrial sites, fibre capacity in underserved regions, OSS automation for smaller operators, edge connectivity for latency-sensitive workloads, or orchestration for multi-vendor networks.

That means choosing a narrow category entry point, building a strong point of view around it, creating the basic evidence needed to support it, and targeting the media, analysts and buyer communities that actually shape that market. Untapped brands have one advantage: less baggage. They can move quickly, define a sharp territory and attach themselves to an emerging issue before larger players converge. But they cannot afford to be vague.

The communications job, by quadrant
QuadrantCore challengePriority
TitansFame can become vagueDefend category meaning
Sleeping GiantsAuthority is hard to retrieveClarify and structure
Algorithmic DisruptorsRecommendation lacks reassuranceBuild human trust
The UntappedFocus is too diffuseChoose one territory
Quick diagnostic

Which quadrant does your brand sit in?

Four questions. Not a substitute for an audit, but a useful place to start.

Buyers in your priority category name you unprompted when the need arises.

Your brand is regularly present in the trade media, events and analyst conversations your buyers follow.

When you prompt ChatGPT, Gemini, Copilot or Perplexity for vendors in your category, your brand appears.

Your strongest technical proof is public, structured and ungated rather than sitting behind a form.

Answer all four to see the likely quadrant, and the communications job that comes with it.

The playbook

How telecoms PR builds visibility with both buyers and AI

The answer to the AI availability challenge isn't to suddenly do everything for machines. You shouldn't be looking at a standalone GEO project, producing SEO content, chasing more mentions or optimising every page on your website in the hope that an AI tool eventually picks it up.

The better response is more strategic and disciplined. Telecoms brands need to use the full PR and marketing mix with a clearer sense of purpose: to become known for a specific problem, understood in the right context, and trusted enough to be chosen when the shortlist is built. Thought leadership, announcements, research, analyst relations, events, owned content and executive profiling all have a very specific role to play, and it should all compound around the same strategic territory.

Start with the buying situation, not the service

The strongest programmes begin with the problem the market is trying to solve. Not just connectivity, but connectivity for which workloads, locations, risks and users. Not just BSS, but BSS for which commercial model, customer experience issue or monetisation challenge. Buying situations create memory, and they create better AI prompts too.

Make the proof points compound

Most telecoms brands already have useful proof points, but they appear at disconnected moments. A new PoP here, a customer signed there, a product launch, a partner announcement, an analyst briefing, a byline, a conference panel. A provider trying to own route resilience should treat all of these as weight behind the same idea. Repetition without proof becomes noise. Proof without repetition is easily missed.

Use opinion-led PR to make the market care

Not the generic kind that says a trend is important, and not the committee-approved byline that could have been written by anyone. The useful kind: timely, human, opinionated and clear about what buyers should pay attention to. Spokespeople generate huge insight from sales meetings, board meetings, R&D teams and customer conversations. The job is to capture it, shape it into a clear point of view and turn it into stories consistently.

React to the news agenda selectively

A cable outage, AI infrastructure announcement, data-centre planning debate, cyber incident, regulatory shift or major M&A story might all create opportunities. That doesn't mean every brand should comment on every story. Ask whether the moment reinforces a buying situation you want to own, whether you have a right to speak, and whether you can add something useful. If not, it's just noise.

Use research to create the category

Hard-hitting research gives shape to a problem the market has not fully named yet. It should expose a tension, quantify a readiness gap, create a headline, give journalists and analysts something useful and arm spokespeople with a point of view. One flagship project can fuel a whitepaper, blogs, social content, videos, sales tools, announcements, interviews and long-term data to respond to market developments.

Make the proof easy to find

Gating reports has long been a tactic for building pipeline, but making that content public makes it easier for everyone to access, including buyers, customers, AI systems, analysts and journalists. Too many important claims live in PDFs, sales decks, gated reports, internal documents or old campaign pages. A brand cannot be understood if its proof is difficult to find. If your sales team relies on gated content, it's worth A/B testing the approach.

Measurement

Are you being found, and are you being recommended?

Traditional PR metrics still have a role. Coverage, share of voice, message pull-through, event visibility and executive profile all help show whether a brand is present in the market. The issue is that presence alone does not tell us whether the brand is being understood in the right context.

A company might be highly visible in trade media and still fail to appear when a buyer asks an AI tool about private 5G, cloud interconnect, BSS modernisation or route resilience. It might be familiar to the market, yet weakly associated with the specific problem it wants to own. It might even appear in AI-generated recommendations while being described through old, incomplete or overly generic language. That is the new measurement gap.

DimensionThe question to ask
VisibilityAre we present in the right conversations?
Category associationAre we known for the right problem?
AI recommendationAre we retrieved for priority buyer prompts?
Description accuracyAre we being described correctly?
Source authorityWhat evidence is shaping the answer?
Human trustAre we credible enough to make the shortlist?

This is where share of recommendation becomes a useful complement to share of voice. Used properly, it shows whether the brand is being retrieved for the right problems, against the right competitors and with the right evidence behind it.

It also helps diagnose what to do next. A brand that is absent from AI recommendations may need clearer content and stronger external signals. A brand that appears but is misunderstood may need sharper messaging, cleaner brand architecture and better source-of-truth material. A brand that is recommended but still struggles to progress may need customer proof, analyst validation and stronger executive visibility.

We're trialling all sorts of LLM measurement to help our clients answer these questions at Babel. More to come on that soon.

Who we are

We turned the lens on ourselves first

At Babel, we've always been driven by insatiable curiosity, never more so than with the relentless march of AI, and how it has fundamentally changed our industry (for the better?). We're basically obsessed with knowing what comes next, which is why we find ourselves where we are today.

For almost twenty years, we were known as a specialist tech PR agency. But, in a bid to deliver brave, consistent and memorable brand narratives across all stages of the marketing funnel, we've successfully transitioned into a full-service B2B powerhouse.

Our 'Back Your Brave' positioning isn't just a tagline; it's a cultural manifesto to help a whole generation of marketers find their voice and build long-term pipelines that actually last.

The Babel team
Conclusion

Known, understood, chosen

Telecoms has always been a trust market. AI doesn't change that, but it does change how brands enter the conversation.

Neither noise nor fame is the right north star for communications in this context. The most successful brands will be the ones buyers remember for the right reasons, machines retrieve for the right problems, and the market can believe when the shortlist is built.

That is the new standard for telecoms reputation.

Known by buyers, understood by machines, and chosen with confidence.

Let's talk

Curious where your telecoms brand stands?

We'll use the Mental Av-AI-lability Index methodology to assess your brand's position across both axes, then show you what it would take to close the gap.

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FAQs

Frequently asked questions

What is the difference between mental availability and AI availability?

Mental availability is the likelihood that a buyer will think of a brand when a relevant buying situation arises. AI availability, sometimes called algorithmic availability, is the likelihood that AI tools will surface or recommend that brand when a buyer uses them to research the same situation. The two are increasingly connected but they are not the same thing: one determines whether a brand comes to mind, while the other influences whether it enters the machine-generated consideration set.

What are category entry points, and why do they matter in telecoms?

Category entry points are the specific buying situations, needs or problems that prompt a buyer to consider a category and, ultimately, particular brands within it. In telecoms that might be needing more resilient international connectivity, private 5G across an industrial site, or connecting data centres to multiple cloud providers. The stronger the association between a brand and these situations, the more likely it is to enter consideration when that need arises, for both human buyers and AI tools.

Why are some famous telecoms brands invisible to AI tools?

Broad portfolios, fragmented product lines and generic language around transformation, connectivity or digital infrastructure make it harder for machines to associate a brand with specific buyer problems. Substance is often present but difficult to find, inconsistently described or buried behind complicated brand architecture and gated content. These brands sit in the Sleeping Giants quadrant: recognised by buyers, but not consistently retrieved by AI for specialist or emerging use cases.

What is share of recommendation?

Share of recommendation measures how often a brand is retrieved and recommended by AI tools for the buyer prompts that matter to it, and how accurately it is described when it appears. It complements share of voice by showing whether a brand is present in the machine-generated consideration set, against the right competitors and with the right evidence behind it, rather than simply present in the market.

How should a telecoms brand start improving its AI visibility?

Start with the buying situation rather than the service, then build a visible evidence trail behind the claim: network expansion announcements, capacity upgrades, customer deployments, performance data, interoperability testing, analyst validation, standards work, technical explainers and proprietary research. Make that proof public, clear and structured rather than locked in PDFs, sales decks or gated reports, and keep every activity compounding around the same strategic territory.

Babel is the agency for B2B tech brands ready to move faster. We combine 20 years of deep sector insight with integrated creative strategies.

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