AI search is not a new technical channel
It is tempting to treat AI search as another box to tick: add a file, install a package and wait for the citations to appear. It does not work like that. An AI answer is assembled from information the system can discover, interpret and trust. Umbraco can give you an excellent foundation, but the CMS cannot compensate for vague pages, buried evidence or a website that says the same thing as everyone else.
The useful question is therefore not ‘How do we optimise Umbraco for ChatGPT?’ It is ‘How do we make our organisation the clearest and most credible answer to the questions our customers ask?’ That changes the work from a technical trick into a content, architecture and evidence problem.
Start with questions, not keywords
Traditional keyword research is still useful, but AI searches are often longer and more specific. A buyer may ask which CMS suits a healthcare group with several locations, whether an Umbraco 13 site should be upgraded or rebuilt, or which UK agency can add semantic search without locking the organisation into one model provider.
Map those real questions to dedicated pages. Give each page a clear purpose and answer the central question early. A concise opening answer helps both people and machines establish what the page is about; the detail underneath earns the trust.
Make the content structure do some work
Umbraco is particularly strong when content is modeled as information rather than stored as one large block of formatted text. Use distinct fields for authors, dates, services, locations, FAQs, credentials, outcomes and related case studies. Keep heading levels logical and expose meaningful relationships between pages.
That structure makes content easier to reuse, govern and mark up. It also reduces ambiguity. A model should not have to infer whether a number is a project result, a price, a date or a claim copied into a decorative banner.
Publish evidence that deserves to be cited
Generic advice is easy to produce and easy to ignore. Original evidence is different. Explain what you tested, what changed and what did not. Add named authors with relevant experience. Use specific case studies, measured outcomes, comparison criteria and clear dates. Where a claim comes from elsewhere, link to the primary source.
This is also where restraint matters. Unsupported superlatives such as ‘leading’, ‘revolutionary’ and ‘best-in-class’ create noise. A plain account of a difficult migration, the decisions made and the result is far more useful.
Remove the technical obstacles
Important pages should return clean server-rendered HTML, load quickly and be reachable through ordinary internal links. Check canonical tags, redirects, robots rules, XML sitemaps and accidental no index directives. Do not hide essential answers behind forms, scripts or an interface that requires several interactions before any text appears.
Add schema where it accurately describes the page, such as Organisation, Article, BreadcrumbList, Person or FAQPage, but do not mistake markup for proof. Structured data clarifies content; it does not make weak content authoritative.
Treat visibility as an ongoing test
Choose a set of commercially relevant questions and test them regularly across the answer engines your audience uses. Record whether your organisation appears, which pages are cited, which competitors are mentioned and whether the answer is accurate. Then improve the missing evidence or unclear content behind the result.
The strongest Umbraco AI-search strategy is not a one-off optimisation project. It is a publishing discipline: answer better questions, structure the answers properly, show your working and keep the evidence current.
A useful next step
Want to know whether your Umbraco site is giving answer engines enough to work with? We can audit the content, technical setup and evidence behind it, and prioritise the changes most likely to matter.