You're findable, but not being recommended
- Traditional search rankings look reasonable but AI tools don't mention the business at all.
- When AI tools do mention the business, the information is outdated or inaccurate.
- Competitors are being cited and recommended in AI-generated answers and the business isn't.
- Content exists but isn't structured in a way machines can reliably extract or cite.
- Nobody in the organisation is actually monitoring how AI systems represent the business.
Structuring for humans and machines together
01
Why this is now a visibility gap, not a novelty
A growing share of research and buying journeys now start inside an AI tool rather than a traditional search engine. A business that is invisible or misrepresented there is losing consideration before a human ever reaches its website.
02
Auditing current AI visibility
Direct-answer testing across major AI tools against the questions real buyers actually ask, to establish what is currently being said — accurately or otherwise.
03
Structural and evidentiary fixes
Clear direct-answer content, accurate and complete structured data, and evidence that AI systems can confidently extract and cite without ambiguity.
04
Governance, not a one-off project
AI systems change without notice. Ongoing monitoring and periodic re-testing keep visibility accurate as both the business and the underlying AI tools evolve.
05
Where this connects to the wider brand
AI visibility work only holds up when it's built on accurate positioning and honest proof — which is why this discipline sits alongside, not apart from, the rest of XL's marketing work.
Proof this is work XL has done
This website itself was rebuilt around structured data, direct-answer content and machine-readable evidence as a working demonstration of the discipline.
The free AI Visibility diagnostic tool was built to give any business a first, structured read on its own AI search standing.
Decades of translating complex, technical propositions into language both people and systems can parse — from telecoms infrastructure to fintech.
Direct build and application of the Decision-Led Growth framework, developed specifically for how AI systems evaluate and cite evidence.
What you receive
A review of how search and AI systems currently find, understand and describe your business, across the six levers. A cornerstone topic chosen for commercial relevance, with the article researched, written and published. Three supporting briefs or derivative assets. On-page structure, internal linking, and author, evidence and citation signals. A measurement baseline and 90-day learning plan.
Available as an AI Visibility & Authority Content Sprint, or as continuing work within a partnership.
The AI Visibility & Authority Content Sprint
Know your subject but not showing up for it? This Sprint answers one question in two to four weeks, from $8,500: which question should this brand become the credible answer to, and what evidence, expertise and structure will earn it that position?
Questions worth answering directly
What is AI search visibility?
AI search visibility is whether a business is accurately found, represented, cited and recommended when people ask AI systems such as ChatGPT, Perplexity and Gemini questions relevant to that business, rather than only appearing in traditional search-engine results pages.
How is AI search different from traditional SEO?
Traditional SEO optimises for ranking positions on a results page a person scans. AI search optimises for being accurately understood, cited and synthesised into a direct answer a person reads without ever visiting the source page. The underlying disciplines overlap but the goal and measurement differ.
What is generative engine optimisation?
Generative engine optimisation, sometimes called answer engine optimisation, is the practice of structuring content, evidence and technical markup so that AI systems can accurately extract, cite and recommend a business within generated answers.
Can you guarantee citation by a specific AI tool?
No credible practitioner can guarantee citation by a specific AI system, since these systems are proprietary and change without notice. What can be improved deliberately is the clarity, structure and evidentiary strength of the content those systems draw on.
How do you measure AI search visibility?
Measurement includes direct-answer testing across major AI tools, citation tracking, structured-data validation, and monitoring whether the business is accurately represented when relevant questions are asked, alongside traditional organic-search indicators.
Ready to see how AI systems currently represent your business?
The first conversation is a structured discussion about the decision, the evidence behind it and the next move — not an immediate proposal.