Can AI navigate your telco website? The connection and visibility test every operator must pass

When AI crawlers visit your website, they usually start at the homepage. However, customer queries are detailed and contextual, such as "best mobile plan for frequent travel to Europe with high data usage".

Most telecoms websites still rely on human-style navigation that AI agents cannot easily follow, leaving relevant answers buried.

This is the connection problem. But even if you solve it, there's a second, more fundamental challenge: visibility. Together, these two challenges determine whether AI even knows you exist.

The Connection Problem: When AI Can't Navigate, It Moves On

Your website was built for humans. Humans understand dropdown menus, product categories, and marketing language. They can click through multiple pages to find what they need.

AI agents don't work that way.

When an AI assistant needs to answer a customer's query, it needs to move quickly from your homepage to the exact page that contains the answer. If your information architecture doesn't support that journey, the AI simply moves on to a competitor whose site structure is clearer.

The Strategic Response: Design for AI, Not Just for Humans

AI discovery requires the same clarity and hierarchy that great UX demands, but designed for machines as well as humans.

• Build clear pathways from homepage to deep, query-specific pages around user intent and long-form queries, not product menus.

• Embed context-rich, machine-readable information on every product or service page.

• Optimise internal linking so AI agents can understand how topics connect.

Operator A's website architecture now mirrors real-world intent. AI agents can move easily from homepage to detailed answers on coverage, pricing, or product bundles.

Operator B's site remains static and difficult for AI to navigate. Customers' detailed queries lead nowhere useful.

The Visibility Problem: If You're Not in the AI's Answer, You Don't Exist

Here's the uncomfortable truth: when a customer asks "Which UK mobile network offers the best rural coverage?", AI assistants rarely crawl individual brand sites. They gather data from comparison tools, press coverage, and review aggregators.

In this environment, there is no "page one"—there is only the answer. If your brand is not cited, it is not seen.

Traditional SEO optimised for getting you onto page one of search results. AI discovery is different. There is no page one. There is no page two. There is only whether you appear in the single synthesised answer the AI provides.

The Strategic Response: Optimise for AI Visibility

Visibility in the AI era means being citable by algorithms, not just clickable by humans.

• Deploy Generative Search Optimisation (GSO) to feed AI platforms with accurate, current content at scale.

• Implement AI PR Monitoring to track when and how your brand is referenced across AI-generated responses.

• Publish structured, AI-readable data using llms.txt and llms-full.txt files.

• Ensure your CMS supports AI-friendly indexing and schema markup.

Operator A uses AI PR Monitoring and Generative Search Optimisation to ensure structured data feeds into every relevant AI query. They are visible wherever customers ask questions.

Operator B has no AI-friendly content policies or structured data files. Their brand is invisible in most AI-mediated conversations.

Where You Can Influence AI Opinions

AI systems don't just learn once—they learn constantly, from multiple entry points. Each one is an opportunity for influence.

Understanding these entry points is essential to shaping how AI systems learn, recall, and represent your organisation.

Now: Content Crawlers

Teach AI who you are.

What: AI-friendly content policies, llms-full.txt files
Where: Public-facing websites and CMS controls
Purpose: To gather data for model training and general knowledge.

Now: Agent Bots

Teach AI who you are.

What: AI-friendly content policies, llms.txt, Q&A pairs, and structured content
Where: Public websites and CMS controls
Purpose: To power real-time user queries drawn from web search indices.

Soon: Structured Feeds

Feed AI what you sell.

What: Google Shopping Feed (AI Mode), ACP Product Feed (OpenAI)
Where: Google Merchant Centre, ACP, and Product Information Management (PIM) systems
Purpose: To provide structured data directly to model repositories for product visibility.

Soon: Advertising

Feed AI what you sell.

What: Sponsored queries and sponsored placement
Where: Google, Perplexity, and demand-side platforms
Purpose: To deliver paid, contextual content directly within conversational AI environments.

Later: Adaptive Content

Let AI talk directly to your systems.

What: Content graph or retrieval-augmented generation (RAG) interfaces, A2A (Agent-to-Agent) APIs
Where: CMS, PIM, and functional applications
Purpose: To deliver dynamic, adaptive content that AI systems can query directly in real time.

The operators that start building these capabilities now will own the future of AI-mediated discovery. Everyone else will be invisible—not to customers, but to the algorithms that decide what customers see. MSQ DX help operators stay visible in the AI era.

Let's deliver impact.